{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/softmax/papers/136","list_of":"/method/softmax","method":"Softmax","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":136,"pages_in_order":375,"rows_per_page":100,"rows":[13501,13600],"of":37443,"counts":{"archive_papers_tagged":37443,"with_a_code_link":15869,"where_syntology_ran_a_sample":4578,"not_listed_spam_title":0,"listed":37443,"listed_where_code_ran":4578,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3835,"every_run_a_failure_of_syntologys_instrument":743,"listed_with_a_run_with_no_instrument_failure":3835,"listed_every_run_a_failure_of_syntologys_instrument":743,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/softmax","prev":"/method/softmax/papers/135","next":"/method/softmax/papers/137","papers":[{"paper":null,"slug":"liveness-detection-in-computer-vision","title":"Liveness Detection in Computer Vision: Transformer-based Self-Supervised Learning for Face Anti-Spoofing","date":"2024-06-19","arxiv_id":"2406.13860","n_code_links":0,"syntology":null},{"paper":null,"slug":"m3t-multi-modal-medical-transformer-to-bridge","title":"M3T: Multi-Modal Medical Transformer to bridge Clinical Context with Visual Insights for Retinal Image Medical Description Generation","date":"2024-06-19","arxiv_id":"2406.13129","n_code_links":0,"syntology":null},{"paper":null,"slug":"mmte-corpus-and-metrics-for-evaluating","title":"MMTE: Corpus and Metrics for Evaluating Machine Translation Quality of Metaphorical Language","date":"2024-06-19","arxiv_id":"2406.13698","n_code_links":0,"syntology":null},{"paper":"/paper/model-internals-based-answer-attribution-for","slug":"model-internals-based-answer-attribution-for","title":"Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation","date":"2024-06-19","arxiv_id":"2406.13663","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["betswish/mirage"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/morehopqa-more-than-multi-hop-reasoning","slug":"morehopqa-more-than-multi-hop-reasoning","title":"MoreHopQA: More Than Multi-hop Reasoning","date":"2024-06-19","arxiv_id":"2406.13397","n_code_links":1,"syntology":null},{"paper":"/paper/multi-meta-rag-improving-rag-for-multi-hop","slug":"multi-meta-rag-improving-rag-for-multi-hop","title":"Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata","date":"2024-06-19","arxiv_id":"2406.13213","n_code_links":1,"syntology":null},{"paper":"/paper/obscureprompt-jailbreaking-large-language","slug":"obscureprompt-jailbreaking-large-language","title":"Jailbreaking Large Language Models Through Alignment Vulnerabilities in Out-of-Distribution Settings","date":"2024-06-19","arxiv_id":"2406.13662","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["HowieHwong/ObscurePrompt"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/on-ai-inspired-ui-design","slug":"on-ai-inspired-ui-design","title":"On AI-Inspired UI-Design","date":"2024-06-19","arxiv_id":"2406.13631","n_code_links":1,"syntology":null},{"paper":null,"slug":"open-generative-large-language-models-for","title":"Open Generative Large Language Models for Galician","date":"2024-06-19","arxiv_id":"2406.13893","n_code_links":0,"syntology":null},{"paper":"/paper/part-aware-unified-representation-of-language-1","slug":"part-aware-unified-representation-of-language-1","title":"Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition","date":"2024-06-19","arxiv_id":"2406.13327","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["azzh1/purls"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/patholm-identifying-pathogenicity-from-the","slug":"patholm-identifying-pathogenicity-from-the","title":"PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model","date":"2024-06-19","arxiv_id":"2406.13133","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Sajib-006/Patho-LM"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/r-2ag-incorporating-retrieval-information","slug":"r-2ag-incorporating-retrieval-information","title":"R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation","date":"2024-06-19","arxiv_id":"2406.13249","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":0,"n_instrument":2,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["yefd/RRAG"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"research-on-fusing-topological-data-analysis","title":"Research on fusing topological data analysis with convolutional neural network","date":"2024-06-19","arxiv_id":"2407.09518","n_code_links":0,"syntology":null},{"paper":null,"slug":"robgc-towards-robust-graph-condensation","title":"RobGC: Towards Robust Graph Condensation","date":"2024-06-19","arxiv_id":"2406.13200","n_code_links":0,"syntology":null},{"paper":"/paper/sali-short-term-alignment-and-long-term-1","slug":"sali-short-term-alignment-and-long-term-1","title":"SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation","date":"2024-06-19","arxiv_id":"2406.13532","n_code_links":1,"syntology":null},{"paper":null,"slug":"sparse-high-rank-adapters","title":"Sparse High Rank Adapters","date":"2024-06-19","arxiv_id":"2406.13175","n_code_links":0,"syntology":null},{"paper":"/paper/stablesemantics-a-synthetic-language-vision","slug":"stablesemantics-a-synthetic-language-vision","title":"StableSemantics: A Synthetic Language-Vision Dataset of Semantic Representations in Naturalistic Images","date":"2024-06-19","arxiv_id":"2406.13735","n_code_links":1,"syntology":null},{"paper":"/paper/strengthening-layer-interaction-via-dynamic","slug":"strengthening-layer-interaction-via-dynamic","title":"Strengthening Layer Interaction via Dynamic Layer Attention","date":"2024-06-19","arxiv_id":"2406.13392","n_code_links":1,"syntology":{"ran":13,"of":14,"n_ran_checked":7,"n_instrument":6,"unverified":1,"pointer_only":14,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","official":{"repos":["tunantu/dynamic-layer-attention"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"swinstyleformer-is-a-favorable-choice-for","title":"SwinStyleformer is a favorable choice for image inversion","date":"2024-06-19","arxiv_id":"2406.13153","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-holistic-language-video","title":"Towards Holistic Language-video Representation: the language model-enhanced MSR-Video to Text Dataset","date":"2024-06-19","arxiv_id":"2406.13809","n_code_links":0,"syntology":null},{"paper":"/paper/ultra-high-definition-restoration-new","slug":"ultra-high-definition-restoration-new","title":"Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution","date":"2024-06-19","arxiv_id":"2406.13607","n_code_links":1,"syntology":null},{"paper":null,"slug":"understanding-the-rope-extensions-of-long","title":"Understanding the RoPE Extensions of Long-Context LLMs: An Attention Perspective","date":"2024-06-19","arxiv_id":"2406.13282","n_code_links":0,"syntology":null},{"paper":"/paper/unveiling-the-hidden-structure-of-self","slug":"unveiling-the-hidden-structure-of-self","title":"Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis","date":"2024-06-19","arxiv_id":"2406.13762","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["rachtsy/kpca_code"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/when-parts-are-greater-than-sums-individual","slug":"when-parts-are-greater-than-sums-individual","title":"When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models","date":"2024-06-19","arxiv_id":"2406.13131","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"0 ran · 1 unverified","official":{"repos":["terarachang/LLMDecomp"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"wikicontradict-a-benchmark-for-evaluating","title":"WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia","date":"2024-06-19","arxiv_id":"2406.13805","n_code_links":0,"syntology":null},{"paper":"/paper/a-neural-column-generation-approach-to-the","slug":"a-neural-column-generation-approach-to-the","title":"A Neural Column Generation Approach to the Vehicle Routing Problem with Two-Dimensional Loading and Last-In-First-Out Constraints","date":"2024-06-18","arxiv_id":"2406.12454","n_code_links":1,"syntology":{"ran":5,"of":6,"n_ran_checked":4,"n_instrument":1,"unverified":1,"pointer_only":6,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["xyfffff/NCG-for-2L-CVRP"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/abnet-attention-barriernet-for-safe-and","slug":"abnet-attention-barriernet-for-safe-and","title":"ABNet: Attention BarrierNet for Safe and Scalable Robot Learning","date":"2024-06-18","arxiv_id":"2406.13025","n_code_links":1,"syntology":null},{"paper":"/paper/adr-attention-diversification-regularization","slug":"adr-attention-diversification-regularization","title":"AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification","date":"2024-06-18","arxiv_id":"2406.15303","n_code_links":3,"syntology":{"ran":12,"of":12,"n_ran_checked":10,"n_instrument":2,"unverified":0,"pointer_only":12,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["dazhangyu123/adr","dazhangyu123/aem"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/agla-mitigating-object-hallucinations-in","slug":"agla-mitigating-object-hallucinations-in","title":"AGLA: Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention","date":"2024-06-18","arxiv_id":"2406.12718","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":0,"n_instrument":4,"unverified":2,"pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","official":{"repos":["lackel/agla"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"an-empirical-study-on-the-fairness-of","title":"An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation","date":"2024-06-18","arxiv_id":"2406.12646","n_code_links":0,"syntology":null},{"paper":"/paper/an-investigation-of-neuron-activation-as-a","slug":"an-investigation-of-neuron-activation-as-a","title":"An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMs","date":"2024-06-18","arxiv_id":"2406.12288","n_code_links":2,"syntology":{"ran":34,"of":36,"n_ran_checked":32,"n_instrument":2,"unverified":2,"pointer_only":12,"phrase":"34 ran (of which 0 constructed an object rather than computing a result; 32 with no instrument failure: 0 honoured, 3 violated, 29 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["dakingrai/neuron-analysis-cot-arithmetic-reasoning"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"assessing-ai-vs-human-authored-spear-phishing","title":"Assessing AI vs Human-Authored Spear Phishing SMS Attacks: An Empirical Study","date":"2024-06-18","arxiv_id":"2406.13049","n_code_links":0,"syntology":null},{"paper":"/paper/attention-score-is-not-all-you-need-for-token","slug":"attention-score-is-not-all-you-need-for-token","title":"Attention Score is not All You Need for Token Importance Indicator in KV Cache Reduction: Value Also Matters","date":"2024-06-18","arxiv_id":"2406.12335","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":4,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["guozhiyu/vatp"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"binaural-selective-attention-model-for-target","title":"Binaural Selective Attention Model for Target Speaker Extraction","date":"2024-06-18","arxiv_id":"2406.12236","n_code_links":0,"syntology":null},{"paper":"/paper/can-large-language-models-always-solve-easy","slug":"can-large-language-models-always-solve-easy","title":"Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones?","date":"2024-06-18","arxiv_id":"2406.12809","n_code_links":1,"syntology":{"ran":11,"of":14,"n_ran_checked":11,"n_instrument":0,"unverified":3,"pointer_only":4,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["QwenLM/ConsisEval"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/chatglm-a-family-of-large-language-models","slug":"chatglm-a-family-of-large-language-models","title":"ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools","date":"2024-06-18","arxiv_id":"2406.12793","n_code_links":7,"syntology":{"ran":21,"of":29,"n_ran_checked":20,"n_instrument":1,"unverified":8,"pointer_only":1,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 20 with no instrument failure: 0 honoured, 0 violated, 20 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["thudm/chatglm-6b"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"competitive-learning-for-achieving-content","title":"Competitive Learning for Achieving Content-specific Filters in Video Coding for Machines","date":"2024-06-18","arxiv_id":"2406.12367","n_code_links":0,"syntology":null},{"paper":"/paper/cyclic-2-5d-perceptual-loss-for-cross-modal","slug":"cyclic-2-5d-perceptual-loss-for-cross-modal","title":"Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET","date":"2024-06-18","arxiv_id":"2406.12632","n_code_links":1,"syntology":null},{"paper":null,"slug":"d2o-dynamic-discriminative-operations-for","title":"D2O: Dynamic Discriminative Operations for Efficient Generative Inference of Large Language Models","date":"2024-06-18","arxiv_id":"2406.13035","n_code_links":0,"syntology":null},{"paper":"/paper/dart-math-difficulty-aware-rejection-tuning-1","slug":"dart-math-difficulty-aware-rejection-tuning-1","title":"DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving","date":"2024-06-18","arxiv_id":"2407.13690","n_code_links":1,"syntology":{"ran":10,"of":12,"n_ran_checked":10,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["hkust-nlp/dart-math"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/efficient-and-long-tailed-generalization-for","slug":"efficient-and-long-tailed-generalization-for","title":"Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model","date":"2024-06-18","arxiv_id":"2406.12638","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":0,"n_instrument":4,"unverified":2,"pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","official":{"repos":["shijxcs/candle"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/emo-know-a-large-scale-dataset-on-emotion-and","slug":"emo-know-a-large-scale-dataset-on-emotion-and","title":"EMO-KNOW: A Large Scale Dataset on Emotion and Emotion-cause","date":"2024-06-18","arxiv_id":"2406.12389","n_code_links":1,"syntology":null},{"paper":null,"slug":"evolutionary-spiking-neural-networks-a-survey","title":"Evolutionary Spiking Neural Networks: A Survey","date":"2024-06-18","arxiv_id":"2406.12552","n_code_links":0,"syntology":null},{"paper":null,"slug":"federated-learning-with-limited-node-labels","title":"Federated Learning with Limited Node Labels","date":"2024-06-18","arxiv_id":"2406.12435","n_code_links":0,"syntology":null},{"paper":null,"slug":"flee-the-flaw-annotating-the-underlying-logic","title":"Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling","date":"2024-06-18","arxiv_id":"2406.12402","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-rags-to-rich-parameters-probing-how","title":"From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries","date":"2024-06-18","arxiv_id":"2406.12824","n_code_links":0,"syntology":null},{"paper":null,"slug":"generating-educational-materials-with","title":"Generating Educational Materials with Different Levels of Readability using LLMs","date":"2024-06-18","arxiv_id":"2406.12787","n_code_links":0,"syntology":null},{"paper":null,"slug":"generative-artificial-intelligence-guided","title":"Generative Artificial Intelligence-Guided User Studies: An Application for Air Taxi Services","date":"2024-06-18","arxiv_id":"2406.12296","n_code_links":0,"syntology":null},{"paper":"/paper/hierarchical-associative-memory-parallelized","slug":"hierarchical-associative-memory-parallelized","title":"Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breaking","date":"2024-06-18","arxiv_id":"2406.12220","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["Toshihiro-Ota/paramixer"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/improving-multi-modal-recommender-systems-by","slug":"improving-multi-modal-recommender-systems-by","title":"Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback","date":"2024-06-18","arxiv_id":"2406.12501","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["enoche/mmrec"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"intermediate-distillation-data-efficient","title":"Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval","date":"2024-06-18","arxiv_id":"2406.12169","n_code_links":0,"syntology":null},{"paper":"/paper/interpretable-preferences-via-multi-objective","slug":"interpretable-preferences-via-multi-objective","title":"Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts","date":"2024-06-18","arxiv_id":"2406.12845","n_code_links":2,"syntology":{"ran":9,"of":9,"n_ran_checked":9,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["RLHFlow/RLHF-Reward-Modeling"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"interpreting-bias-in-large-language-models-a","title":"Interpreting Bias in Large Language Models: A Feature-Based Approach","date":"2024-06-18","arxiv_id":"2406.12347","n_code_links":0,"syntology":null},{"paper":"/paper/ipeval-a-bilingual-intellectual-property","slug":"ipeval-a-bilingual-intellectual-property","title":"IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models","date":"2024-06-18","arxiv_id":"2406.12386","n_code_links":1,"syntology":null},{"paper":"/paper/judging-the-judges-evaluating-alignment-and","slug":"judging-the-judges-evaluating-alignment-and","title":"Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges","date":"2024-06-18","arxiv_id":"2406.12624","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["UMass-Meta-LLM-Eval/llm_eval"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"licaf-lidar-camera-asymmetric-fusion-for-gait","title":"LiCAF: LiDAR-Camera Asymmetric Fusion for Gait Recognition","date":"2024-06-18","arxiv_id":"2406.12355","n_code_links":0,"syntology":null},{"paper":"/paper/measuring-psychological-depth-in-language","slug":"measuring-psychological-depth-in-language","title":"Measuring Psychological Depth in Language Models","date":"2024-06-18","arxiv_id":"2406.12680","n_code_links":1,"syntology":null},{"paper":"/paper/mixing-natural-and-synthetic-images-for","slug":"mixing-natural-and-synthetic-images-for","title":"MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations","date":"2024-06-18","arxiv_id":"2406.12368","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-robustness-of-language-models-for","title":"Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis","date":"2024-06-18","arxiv_id":"2406.12719","n_code_links":0,"syntology":null},{"paper":null,"slug":"p-tailor-customizing-personality-traits-for","title":"P-Tailor: Customizing Personality Traits for Language Models via Mixture of Specialized LoRA Experts","date":"2024-06-18","arxiv_id":"2406.12548","n_code_links":0,"syntology":null},{"paper":"/paper/pcie-egohandpose-solution-for-egoexo4d-hand","slug":"pcie-egohandpose-solution-for-egoexo4d-hand","title":"PCIE_EgoHandPose Solution for EgoExo4D Hand Pose Challenge","date":"2024-06-18","arxiv_id":"2406.12219","n_code_links":1,"syntology":null},{"paper":"/paper/planrag-a-plan-then-retrieval-augmented","slug":"planrag-a-plan-then-retrieval-augmented","title":"PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers","date":"2024-06-18","arxiv_id":"2406.12430","n_code_links":1,"syntology":{"ran":5,"of":6,"n_ran_checked":5,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["myeon9h/planrag"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"recognition-of-dynamic-hand-gestures-in-long","title":"Recognition of Dynamic Hand Gestures in Long Distance using a Web-Camera for Robot Guidance","date":"2024-06-18","arxiv_id":"2406.12424","n_code_links":0,"syntology":null},{"paper":"/paper/restorer-solving-multiple-image-restoration","slug":"restorer-solving-multiple-image-restoration","title":"Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance","date":"2024-06-18","arxiv_id":"2406.12587","n_code_links":1,"syntology":null},{"paper":null,"slug":"retrieval-augmented-generation-for-generative","title":"Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine","date":"2024-06-18","arxiv_id":"2406.12449","n_code_links":0,"syntology":null},{"paper":null,"slug":"richrag-crafting-rich-responses-for-multi","title":"RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation","date":"2024-06-18","arxiv_id":"2406.12566","n_code_links":0,"syntology":null},{"paper":null,"slug":"saliency-attention-and-semantic-similarity","title":"Saliency Attention and Semantic Similarity-Driven Adversarial Perturbation","date":"2024-06-18","arxiv_id":"2406.19413","n_code_links":0,"syntology":null},{"paper":null,"slug":"sample-efficient-imitative-multi-token","title":"Physics-informed Imitative Reinforcement Learning for Real-world Driving","date":"2024-06-18","arxiv_id":"2407.02508","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-localized-collaborative-perception","title":"Self-Localized Collaborative Perception","date":"2024-06-18","arxiv_id":"2406.12712","n_code_links":0,"syntology":null},{"paper":null,"slug":"spatial-sequence-attention-network-for","title":"Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images","date":"2024-06-18","arxiv_id":"2406.12683","n_code_links":0,"syntology":null},{"paper":"/paper/text-aware-speech-separation-for-multi-talker","slug":"text-aware-speech-separation-for-multi-talker","title":"Text-aware Speech Separation for Multi-talker Keyword Spotting","date":"2024-06-18","arxiv_id":"2406.12447","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-limits-of-pure-exploration-in-pomdps-when","title":"The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough","date":"2024-06-18","arxiv_id":"2406.12795","n_code_links":0,"syntology":null},{"paper":"/paper/towards-a-client-centered-assessment-of-llm","slug":"towards-a-client-centered-assessment-of-llm","title":"Towards a Client-Centered Assessment of LLM Therapists by Client Simulation","date":"2024-06-18","arxiv_id":"2406.12266","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["wangjs9/clientcast"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"traffic-prediction-considering-multiple","title":"Traffic Prediction considering Multiple Levels of Spatial-temporal Information: A Multi-scale Graph Wavelet-based Approach","date":"2024-06-18","arxiv_id":"2406.13038","n_code_links":0,"syntology":null},{"paper":"/paper/translation-equivariant-transformer-neural","slug":"translation-equivariant-transformer-neural","title":"Translation Equivariant Transformer Neural Processes","date":"2024-06-18","arxiv_id":"2406.12409","n_code_links":1,"syntology":null},{"paper":"/paper/ubench-benchmarking-uncertainty-in-large","slug":"ubench-benchmarking-uncertainty-in-large","title":"UBENCH: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions","date":"2024-06-18","arxiv_id":"2406.12784","n_code_links":1,"syntology":null},{"paper":"/paper/unified-active-retrieval-for-retrieval","slug":"unified-active-retrieval-for-retrieval","title":"Unified Active Retrieval for Retrieval Augmented Generation","date":"2024-06-18","arxiv_id":"2406.12534","n_code_links":1,"syntology":null},{"paper":null,"slug":"urbanllm-autonomous-urban-activity-planning","title":"UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models","date":"2024-06-18","arxiv_id":"2406.12360","n_code_links":0,"syntology":null},{"paper":null,"slug":"vernacular-i-barely-know-her-challenges-with","title":"Vernacular? I Barely Know Her: Challenges with Style Control and Stereotyping","date":"2024-06-18","arxiv_id":"2406.12679","n_code_links":0,"syntology":null},{"paper":null,"slug":"via-a-spatiotemporal-video-adaptation","title":"VIA: Unified Spatiotemporal Video Adaptation Framework for Global and Local Video Editing","date":"2024-06-18","arxiv_id":"2406.12831","n_code_links":0,"syntology":null},{"paper":"/paper/voco-llama-towards-vision-compression-with","slug":"voco-llama-towards-vision-compression-with","title":"VoCo-LLaMA: Towards Vision Compression with Large Language Models","date":"2024-06-18","arxiv_id":"2406.12275","n_code_links":1,"syntology":{"ran":12,"of":15,"n_ran_checked":6,"n_instrument":6,"unverified":3,"pointer_only":5,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 6 where Syntology's instrument failed) · 3 unverified","official":{"repos":["Yxxxb/VoCo-LLaMA"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/weakly-supervised-learning-of-cortical","slug":"weakly-supervised-learning-of-cortical","title":"Weakly Supervised Learning of Cortical Surface Reconstruction from Segmentations","date":"2024-06-18","arxiv_id":"2406.12650","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["m-qiang/CoSeg"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"what-makes-two-models-think-alike","title":"What Makes Two Language Models Think Alike?","date":"2024-06-18","arxiv_id":"2406.12620","n_code_links":0,"syntology":null},{"paper":null,"slug":"you-gotta-be-a-doctor-lin-an-investigation-of","title":"\"You Gotta be a Doctor, Lin\": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations","date":"2024-06-18","arxiv_id":"2406.12232","n_code_links":0,"syntology":null},{"paper":"/paper/a-critical-study-of-what-code-llms-do-not","slug":"a-critical-study-of-what-code-llms-do-not","title":"A Critical Study of What Code-LLMs (Do Not) Learn","date":"2024-06-17","arxiv_id":"2406.11930","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-personalised-learning-tool-for-physics","title":"A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression","date":"2024-06-17","arxiv_id":"2407.00065","n_code_links":0,"syntology":null},{"paper":"/paper/a-simple-and-effective-l-2-norm-based","slug":"a-simple-and-effective-l-2-norm-based","title":"A Simple and Effective $L_2$ Norm-Based Strategy for KV Cache Compression","date":"2024-06-17","arxiv_id":"2406.11430","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["alessiodevoto/l2compress"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-two-dimensional-zero-shot-dialogue-state","slug":"a-two-dimensional-zero-shot-dialogue-state","title":"A Two-dimensional Zero-shot Dialogue State Tracking Evaluation Method using GPT-4","date":"2024-06-17","arxiv_id":"2406.11651","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-exploration-of-length-generalization-in","title":"An Exploration of Length Generalization in Transformer-Based Speech Enhancement","date":"2024-06-17","arxiv_id":"2406.11401","n_code_links":0,"syntology":null},{"paper":"/paper/an-online-approach-and-evaluation-method-for","slug":"an-online-approach-and-evaluation-method-for","title":"An Online Approach and Evaluation Method for Tracking People Across Cameras in Extremely Long Video Sequence","date":"2024-06-17","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/are-large-language-models-true-healthcare","slug":"are-large-language-models-true-healthcare","title":"Are Large Language Models True Healthcare Jacks-of-All-Trades? Benchmarking Across Health Professions Beyond Physician Exams","date":"2024-06-17","arxiv_id":"2406.11328","n_code_links":1,"syntology":null},{"paper":null,"slug":"attention-based-deep-reinforcement-learning-1","title":"Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures","date":"2024-06-17","arxiv_id":"2406.11452","n_code_links":0,"syntology":null},{"paper":"/paper/av-crossnet-an-audiovisual-complex-spectral","slug":"av-crossnet-an-audiovisual-complex-spectral","title":"AV-CrossNet: an Audiovisual Complex Spectral Mapping Network for Speech Separation By Leveraging Narrow- and Cross-Band Modeling","date":"2024-06-17","arxiv_id":"2406.11619","n_code_links":1,"syntology":null},{"paper":"/paper/beyond-boundaries-learning-a-universal-entity","slug":"beyond-boundaries-learning-a-universal-entity","title":"Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition","date":"2024-06-17","arxiv_id":"2406.11192","n_code_links":1,"syntology":null},{"paper":null,"slug":"brain-inspired-computational-modeling-of","title":"Brain-inspired Computational Modeling of Action Recognition with Recurrent Spiking Neural Networks Equipped with Reinforcement Delay Learning","date":"2024-06-17","arxiv_id":"2406.11778","n_code_links":0,"syntology":null},{"paper":null,"slug":"breaking-boundaries-investigating-the-effects","title":"Breaking Boundaries: Investigating the Effects of Model Editing on Cross-linguistic Performance","date":"2024-06-17","arxiv_id":"2406.11139","n_code_links":0,"syntology":null},{"paper":null,"slug":"bridging-design-gaps-a-parametric-data","title":"Bridging Design Gaps: A Parametric Data Completion Approach With Graph Guided Diffusion Models","date":"2024-06-17","arxiv_id":"2406.11934","n_code_links":0,"syntology":null},{"paper":"/paper/building-another-spanish-dictionary-this-time","slug":"building-another-spanish-dictionary-this-time","title":"Building another Spanish dictionary, this time with GPT-4","date":"2024-06-17","arxiv_id":"2406.11218","n_code_links":1,"syntology":null},{"paper":"/paper/citrus-chunked-instruction-aware-state","slug":"citrus-chunked-instruction-aware-state","title":"CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling","date":"2024-06-17","arxiv_id":"2406.12018","n_code_links":1,"syntology":{"ran":5,"of":10,"n_ran_checked":0,"n_instrument":5,"unverified":5,"pointer_only":10,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 5 unverified","official":{"repos":["ybai-nlp/CItruS"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/composing-object-relations-and-attributes-for-1","slug":"composing-object-relations-and-attributes-for-1","title":"Composing Object Relations and Attributes for Image-Text Matching","date":"2024-06-17","arxiv_id":"2406.11820","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":1,"n_instrument":3,"unverified":1,"pointer_only":5,"phrase":"4 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["vkhoi/cora_cvpr24"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}}],"record_sha256":"c75057a4b24cbd4a0ca995f14d0fe6928e40429987a9db77f0da7149877fb660","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}