{"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/124","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":124,"pages_in_order":375,"rows_per_page":100,"rows":[12301,12400],"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/123","next":"/method/softmax/papers/125","papers":[{"paper":null,"slug":"large-language-models-as-reliable-knowledge","title":"How Reliable are LLMs as Knowledge Bases? Re-thinking Facutality and Consistency","date":"2024-07-18","arxiv_id":"2407.13578","n_code_links":0,"syntology":null},{"paper":null,"slug":"learn-to-memorize-and-to-forget-a-continual","title":"Learn to Memorize and to Forget: A Continual Learning Perspective of Dynamic SLAM","date":"2024-07-18","arxiv_id":"2407.13338","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-from-mistakes-prompting-for","title":"Learning-From-Mistakes Prompting for Indigenous Language Translation","date":"2024-07-18","arxiv_id":"2407.13343","n_code_links":0,"syntology":null},{"paper":null,"slug":"lsd3k-a-benchmark-for-smoke-removal-from","title":"LSD3K: A Benchmark for Smoke Removal from Laparoscopic Surgery Images","date":"2024-07-18","arxiv_id":"2407.13132","n_code_links":0,"syntology":null},{"paper":null,"slug":"medic-zero-shot-music-editing-with","title":"MEDIC: Zero-shot Music Editing with Disentangled Inversion Control","date":"2024-07-18","arxiv_id":"2407.13220","n_code_links":0,"syntology":null},{"paper":null,"slug":"meshfeat-multi-resolution-features-for-neural","title":"MeshFeat: Multi-Resolution Features for Neural Fields on Meshes","date":"2024-07-18","arxiv_id":"2407.13592","n_code_links":0,"syntology":null},{"paper":"/paper/oat-object-level-attention-transformer-for","slug":"oat-object-level-attention-transformer-for","title":"OAT: Object-Level Attention Transformer for Gaze Scanpath Prediction","date":"2024-07-18","arxiv_id":"2407.13335","n_code_links":1,"syntology":{"ran":15,"of":18,"n_ran_checked":15,"n_instrument":0,"unverified":3,"pointer_only":18,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 1 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["hkust-nisl/oat_eccv24"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"out-of-distribution-detection-through-soft","title":"Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression","date":"2024-07-18","arxiv_id":"2407.13141","n_code_links":0,"syntology":null},{"paper":null,"slug":"pragyan-connecting-the-dots-in-tweets","title":"PRAGyan -- Connecting the Dots in Tweets","date":"2024-07-18","arxiv_id":"2407.13909","n_code_links":0,"syntology":null},{"paper":null,"slug":"qalam-a-multimodal-llm-for-arabic-optical","title":"Qalam : A Multimodal LLM for Arabic Optical Character and Handwriting Recognition","date":"2024-07-18","arxiv_id":"2407.13559","n_code_links":0,"syntology":null},{"paper":null,"slug":"reconstruct-the-pruned-model-without-any","title":"Reconstruct the Pruned Model without Any Retraining","date":"2024-07-18","arxiv_id":"2407.13331","n_code_links":0,"syntology":null},{"paper":null,"slug":"retrieval-augmented-generation-for-natural","title":"Retrieval-Augmented Generation for Natural Language Processing: A Survey","date":"2024-07-18","arxiv_id":"2407.13193","n_code_links":0,"syntology":null},{"paper":null,"slug":"retrieve-summarize-plan-advancing-multi-hop","title":"Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach","date":"2024-07-18","arxiv_id":"2407.13101","n_code_links":0,"syntology":null},{"paper":"/paper/revisiting-attention-for-multivariate-time","slug":"revisiting-attention-for-multivariate-time","title":"Revisiting Attention for Multivariate Time Series Forecasting","date":"2024-07-18","arxiv_id":"2407.13806","n_code_links":1,"syntology":null},{"paper":"/paper/scape-a-simple-and-strong-category-agnostic","slug":"scape-a-simple-and-strong-category-agnostic","title":"SCAPE: A Simple and Strong Category-Agnostic Pose Estimator","date":"2024-07-18","arxiv_id":"2407.13483","n_code_links":1,"syntology":{"ran":7,"of":7,"n_ran_checked":6,"n_instrument":1,"unverified":0,"pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["tiny-smart/SCAPE"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/similarity-over-factuality-are-we-making","slug":"similarity-over-factuality-are-we-making","title":"Similarity over Factuality: Are we making progress on multimodal out-of-context misinformation detection?","date":"2024-07-18","arxiv_id":"2407.13488","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"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":["stevejpapad/outcontext-misinfo-progress"],"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/sustechgan-image-generation-for-object","slug":"sustechgan-image-generation-for-object","title":"SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous Driving","date":"2024-07-18","arxiv_id":"2408.01430","n_code_links":1,"syntology":null},{"paper":"/paper/training-free-composite-scene-generation-for","slug":"training-free-composite-scene-generation-for","title":"Training-free Composite Scene Generation for Layout-to-Image Synthesis","date":"2024-07-18","arxiv_id":"2407.13609","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformer-based-single-cell-language-model","title":"Transformer-based Single-Cell Language Model: A Survey","date":"2024-07-18","arxiv_id":"2407.13205","n_code_links":0,"syntology":null},{"paper":"/paper/transformers-with-stochastic-competition-for","slug":"transformers-with-stochastic-competition-for","title":"Transformers with Stochastic Competition for Tabular Data Modelling","date":"2024-07-18","arxiv_id":"2407.13238","n_code_links":1,"syntology":null},{"paper":null,"slug":"unified-egformer-exposure-guided-lightweight","title":"Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement","date":"2024-07-18","arxiv_id":"2407.13170","n_code_links":0,"syntology":null},{"paper":null,"slug":"unsupervised-and-interpretable-synthesizing","title":"Unsupervised and Interpretable Synthesizing for Electrical Time Series Based on Information Maximizing Generative Adversarial Nets","date":"2024-07-18","arxiv_id":"2407.13691","n_code_links":0,"syntology":null},{"paper":"/paper/wavelet-based-bi-dimensional-aggregation","slug":"wavelet-based-bi-dimensional-aggregation","title":"Wavelet-based Bi-dimensional Aggregation Network for SAR Image Change Detection","date":"2024-07-18","arxiv_id":"2407.13151","n_code_links":1,"syntology":null},{"paper":"/paper/werewolf-arena-a-case-study-in-llm-evaluation","slug":"werewolf-arena-a-case-study-in-llm-evaluation","title":"Werewolf Arena: A Case Study in LLM Evaluation via Social Deduction","date":"2024-07-18","arxiv_id":"2407.13943","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"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":["google/werewolf_arena"],"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/why-do-you-cite-an-investigation-on-citation","slug":"why-do-you-cite-an-investigation-on-citation","title":"Why do you cite? An investigation on citation intents and decision-making classification processes","date":"2024-07-18","arxiv_id":"2407.13329","n_code_links":0,"syntology":null},{"paper":"/paper/2408-00788","slug":"2408-00788","title":"SpikeVoice: High-Quality Text-to-Speech Via Efficient Spiking Neural Network","date":"2024-07-17","arxiv_id":"2408.00788","n_code_links":1,"syntology":null},{"paper":"/paper/adalog-post-training-quantization-for-vision","slug":"adalog-post-training-quantization-for-vision","title":"AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer","date":"2024-07-17","arxiv_id":"2407.12951","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["GoatWu/AdaLog"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/agentpoison-red-teaming-llm-agents-via","slug":"agentpoison-red-teaming-llm-agents-via","title":"AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases","date":"2024-07-17","arxiv_id":"2407.12784","n_code_links":1,"syntology":{"ran":16,"of":19,"n_ran_checked":15,"n_instrument":1,"unverified":3,"pointer_only":1,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 1 honoured, 0 violated, 14 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["BillChan226/AgentPoison"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"artemis-a-mixed-analog-stochastic-in-dram","title":"ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks","date":"2024-07-17","arxiv_id":"2407.12638","n_code_links":0,"syntology":null},{"paper":"/paper/attention-guided-low-rank-tensor-completion","slug":"attention-guided-low-rank-tensor-completion","title":"Attention-Guided Low-Rank Tensor Completion","date":"2024-07-17","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/bsc-upc-at-emospeech-iberlef2024-attention","slug":"bsc-upc-at-emospeech-iberlef2024-attention","title":"BSC-UPC at EmoSPeech-IberLEF2024: Attention Pooling for Emotion Recognition","date":"2024-07-17","arxiv_id":"2407.12467","n_code_links":1,"syntology":null},{"paper":null,"slug":"causality-inspired-discriminative-feature","title":"Causality-inspired Discriminative Feature Learning in Triple Domains for Gait Recognition","date":"2024-07-17","arxiv_id":"2407.12519","n_code_links":0,"syntology":null},{"paper":null,"slug":"clearclip-decomposing-clip-representations","title":"ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference","date":"2024-07-17","arxiv_id":"2407.12442","n_code_links":0,"syntology":null},{"paper":null,"slug":"compound-expression-recognition-via-multi-1","title":"Compound Expression Recognition via Multi Model Ensemble for the ABAW7 Challenge","date":"2024-07-17","arxiv_id":"2407.12257","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-based-sentiment-analysis-of-1","title":"Deep Learning-based Sentiment Analysis of Olympics Tweets","date":"2024-07-17","arxiv_id":"2407.12376","n_code_links":0,"syntology":null},{"paper":"/paper/dual-hybrid-attention-network-for-specular","slug":"dual-hybrid-attention-network-for-specular","title":"Dual-Hybrid Attention Network for Specular Highlight Removal","date":"2024-07-17","arxiv_id":"2407.12255","n_code_links":1,"syntology":null},{"paper":null,"slug":"effects-of-dynamic-power-electronic-load","title":"Effects of dynamic power electronic load models on power systems analysis using ZIP-E loads","date":"2024-07-17","arxiv_id":"2407.12715","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-facial-expression-recognition","title":"Enhancing Facial Expression Recognition through Dual-Direction Attention Mixed Feature Networks: Application to 7th ABAW Challenge","date":"2024-07-17","arxiv_id":"2407.12390","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-wrist-abnormality-detection-with","slug":"enhancing-wrist-abnormality-detection-with","title":"Enhancing Wrist Fracture Detection with YOLO","date":"2024-07-17","arxiv_id":"2407.12597","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploiting-inter-image-similarity-prior-for","title":"Exploiting Inter-Image Similarity Prior for Low-Bitrate Remote Sensing Image Compression","date":"2024-07-17","arxiv_id":"2407.12295","n_code_links":0,"syntology":null},{"paper":null,"slug":"facial-affect-recognition-based-on-multi","title":"Facial Affect Recognition based on Multi Architecture Encoder and Feature Fusion for the ABAW7 Challenge","date":"2024-07-17","arxiv_id":"2407.12258","n_code_links":0,"syntology":null},{"paper":"/paper/frequency-guidance-matters-skeletal-action","slug":"frequency-guidance-matters-skeletal-action","title":"Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed Transformer","date":"2024-07-17","arxiv_id":"2407.12322","n_code_links":1,"syntology":null},{"paper":null,"slug":"fusion-flow-enhanced-graph-pooling-residual","title":"Fusion Flow-enhanced Graph Pooling Residual Networks for Unmanned Aerial Vehicles Surveillance in Day and Night Dual Visions","date":"2024-07-17","arxiv_id":"2407.12647","n_code_links":0,"syntology":null},{"paper":"/paper/global-local-similarity-for-efficient-fine","slug":"global-local-similarity-for-efficient-fine","title":"Global-Local Similarity for Efficient Fine-Grained Image Recognition with Vision Transformers","date":"2024-07-17","arxiv_id":"2407.12891","n_code_links":1,"syntology":null},{"paper":"/paper/gume-graphs-and-user-modalities-enhancement","slug":"gume-graphs-and-user-modalities-enhancement","title":"GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation","date":"2024-07-17","arxiv_id":"2407.12338","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":["nangongningyi/gume"],"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":null,"slug":"hybrid-dynamic-pruning-a-pathway-to-efficient","title":"Hybrid Dynamic Pruning: A Pathway to Efficient Transformer Inference","date":"2024-07-17","arxiv_id":"2407.12893","n_code_links":0,"syntology":null},{"paper":null,"slug":"i2am-interpreting-image-to-image-latent","title":"I2AM: Interpreting Image-to-Image Latent Diffusion Models via Attribution Maps","date":"2024-07-17","arxiv_id":"2407.12331","n_code_links":0,"syntology":null},{"paper":"/paper/imagdressing-v1-customizable-virtual-dressing","slug":"imagdressing-v1-customizable-virtual-dressing","title":"IMAGDressing-v1: Customizable Virtual Dressing","date":"2024-07-17","arxiv_id":"2407.12705","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"4 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["muzishen/imagdressing"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"is-sarcasm-detection-a-step-by-step-reasoning","title":"Is Sarcasm Detection A Step-by-Step Reasoning Process in Large Language Models?","date":"2024-07-17","arxiv_id":"2407.12725","n_code_links":0,"syntology":null},{"paper":null,"slug":"lookupvit-compressing-visual-information-to-a","title":"LookupViT: Compressing visual information to a limited number of tokens","date":"2024-07-17","arxiv_id":"2407.12753","n_code_links":0,"syntology":null},{"paper":null,"slug":"m2ds-multilingual-dataset-for-multi-document","title":"M2DS: Multilingual Dataset for Multi-document Summarisation","date":"2024-07-17","arxiv_id":"2407.12336","n_code_links":0,"syntology":null},{"paper":"/paper/mdpe-a-multimodal-deception-dataset-with","slug":"mdpe-a-multimodal-deception-dataset-with","title":"MDPE: A Multimodal Deception Dataset with Personality and Emotional Characteristics","date":"2024-07-17","arxiv_id":"2407.12274","n_code_links":1,"syntology":null},{"paper":"/paper/object-aware-query-perturbation-for-cross","slug":"object-aware-query-perturbation-for-cross","title":"Object-Aware Query Perturbation for Cross-Modal Image-Text Retrieval","date":"2024-07-17","arxiv_id":"2407.12346","n_code_links":1,"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":["nec-n-sogi/query-perturbation"],"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":"on-initializing-transformers-with-pre-trained","title":"On Initializing Transformers with Pre-trained Embeddings","date":"2024-07-17","arxiv_id":"2407.12514","n_code_links":0,"syntology":null},{"paper":"/paper/open-world-electrocardiogram-classification","slug":"open-world-electrocardiogram-classification","title":"Open-World Electrocardiogram Classification via Domain Knowledge-Driven Contrastive Learning","date":"2024-07-17","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"optimizing-query-generation-for-enhanced","title":"Optimizing Query Generation for Enhanced Document Retrieval in RAG","date":"2024-07-17","arxiv_id":"2407.12325","n_code_links":0,"syntology":null},{"paper":"/paper/safepowergraph-safety-aware-evaluation-of","slug":"safepowergraph-safety-aware-evaluation-of","title":"SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids","date":"2024-07-17","arxiv_id":"2407.12421","n_code_links":1,"syntology":null},{"paper":"/paper/search-engines-llms-or-both-evaluating","slug":"search-engines-llms-or-both-evaluating","title":"Evaluating Search Engines and Large Language Models for Answering Health Questions","date":"2024-07-17","arxiv_id":"2407.12468","n_code_links":1,"syntology":null},{"paper":"/paper/sharif-str-at-semeval-2024-task-1-transformer","slug":"sharif-str-at-semeval-2024-task-1-transformer","title":"Sharif-STR at SemEval-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations","date":"2024-07-17","arxiv_id":"2407.12426","n_code_links":1,"syntology":null},{"paper":null,"slug":"steamroller-problems-an-evaluation-of-llm","title":"Steamroller Problems: An Evaluation of LLM Reasoning Capability with Automated Theorem Prover Strategies","date":"2024-07-17","arxiv_id":"2407.20244","n_code_links":0,"syntology":null},{"paper":null,"slug":"temporal-label-hierachical-network-for","title":"Temporal Label Hierachical Network for Compound Emotion Recognition","date":"2024-07-17","arxiv_id":"2407.12973","n_code_links":0,"syntology":null},{"paper":"/paper/text-and-feature-based-models-for-compound","slug":"text-and-feature-based-models-for-compound","title":"Textualized and Feature-based Models for Compound Multimodal Emotion Recognition in the Wild","date":"2024-07-17","arxiv_id":"2407.12927","n_code_links":2,"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":["nicolas-richet/feature-vs-text-compound-emotion"],"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/uncertainty-calibration-with-energy-based","slug":"uncertainty-calibration-with-energy-based","title":"Uncertainty Calibration with Energy Based Instance-wise Scaling in the Wild Dataset","date":"2024-07-17","arxiv_id":"2407.12330","n_code_links":1,"syntology":null},{"paper":"/paper/variable-agnostic-causal-exploration-for","slug":"variable-agnostic-causal-exploration-for","title":"Variable-Agnostic Causal Exploration for Reinforcement Learning","date":"2024-07-17","arxiv_id":"2407.12437","n_code_links":1,"syntology":null},{"paper":"/paper/visfocus-prompt-guided-vision-encoders-for","slug":"visfocus-prompt-guided-vision-encoders-for","title":"VisFocus: Prompt-Guided Vision Encoders for OCR-Free Dense Document Understanding","date":"2024-07-17","arxiv_id":"2407.12594","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-benchmark-for-fairness-aware-graph-learning","title":"A Benchmark for Fairness-Aware Graph Learning","date":"2024-07-16","arxiv_id":"2407.12112","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-channel-attention-driven-hybrid-cnn","title":"A Channel Attention-Driven Hybrid CNN Framework for Paddy Leaf Disease Detection","date":"2024-07-16","arxiv_id":"2407.11753","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-graph-based-adversarial-imitation-learning","title":"A Graph-based Adversarial Imitation Learning Framework for Reliable & Realtime Fleet Scheduling in Urban Air Mobility","date":"2024-07-16","arxiv_id":"2407.12113","n_code_links":0,"syntology":null},{"paper":null,"slug":"animate3d-animating-any-3d-model-with-multi","title":"Animate3D: Animating Any 3D Model with Multi-view Video Diffusion","date":"2024-07-16","arxiv_id":"2407.11398","n_code_links":0,"syntology":null},{"paper":"/paper/better-rag-using-relevant-information-gain","slug":"better-rag-using-relevant-information-gain","title":"Better RAG using Relevant Information Gain","date":"2024-07-16","arxiv_id":"2407.12101","n_code_links":1,"syntology":null},{"paper":null,"slug":"beyond-binary-multiclass-paraphasia-detection","title":"Beyond Binary: Multiclass Paraphasia Detection with Generative Pretrained Transformers and End-to-End Models","date":"2024-07-16","arxiv_id":"2407.11345","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-spatial-explanations-explainable-face","title":"Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain","date":"2024-07-16","arxiv_id":"2407.11941","n_code_links":0,"syntology":null},{"paper":null,"slug":"chatbcg-can-ai-read-your-slide-deck","title":"ChatBCG: Can AI Read Your Slide Deck?","date":"2024-07-16","arxiv_id":"2407.12875","n_code_links":0,"syntology":null},{"paper":null,"slug":"co-designing-binarized-transformer-and","title":"Co-Designing Binarized Transformer and Hardware Accelerator for Efficient End-to-End Edge Deployment","date":"2024-07-16","arxiv_id":"2407.12070","n_code_links":0,"syntology":null},{"paper":"/paper/continuity-preserving-online-centerline-graph","slug":"continuity-preserving-online-centerline-graph","title":"Continuity Preserving Online CenterLine Graph Learning","date":"2024-07-16","arxiv_id":"2407.11337","n_code_links":1,"syntology":null},{"paper":null,"slug":"cycle-contrastive-adversarial-learning-for","title":"Cycle Contrastive Adversarial Learning for Unsupervised image Deraining","date":"2024-07-16","arxiv_id":"2407.11750","n_code_links":0,"syntology":null},{"paper":null,"slug":"dino-diffusion-scaling-medical-diffusion-via","title":"DiNO-Diffusion. Scaling Medical Diffusion via Self-Supervised Pre-Training","date":"2024-07-16","arxiv_id":"2407.11594","n_code_links":0,"syntology":null},{"paper":"/paper/does-refusal-training-in-llms-generalize-to","slug":"does-refusal-training-in-llms-generalize-to","title":"Does Refusal Training in LLMs Generalize to the Past Tense?","date":"2024-07-16","arxiv_id":"2407.11969","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":3,"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":["tml-epfl/llm-past-tense"],"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/ecoh-turn-level-coherence-evaluation-for","slug":"ecoh-turn-level-coherence-evaluation-for","title":"ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues","date":"2024-07-16","arxiv_id":"2407.11660","n_code_links":1,"syntology":null},{"paper":null,"slug":"educational-personalized-learning-path","title":"Educational Personalized Learning Path Planning with Large Language Models","date":"2024-07-16","arxiv_id":"2407.11773","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-quantization-for-efficient-pre","slug":"exploring-quantization-for-efficient-pre","title":"Exploring Quantization for Efficient Pre-Training of Transformer Language Models","date":"2024-07-16","arxiv_id":"2407.11722","n_code_links":1,"syntology":null},{"paper":null,"slug":"gpt-assisted-annotation-of-rhetorical-and","title":"GPT Assisted Annotation of Rhetorical and Linguistic Features for Interpretable Propaganda Technique Detection in News Text","date":"2024-07-16","arxiv_id":"2407.11827","n_code_links":0,"syntology":null},{"paper":"/paper/gradient-guided-multiscale-focal-attention","slug":"gradient-guided-multiscale-focal-attention","title":"Gradient-Guided Multiscale Focal Attention Network for Remote Sensing Scene Classification","date":"2024-07-16","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"graph-dimension-attention-networks-for","title":"Graph Dimension Attention Networks for Enterprise Credit Assessment","date":"2024-07-16","arxiv_id":"2407.11615","n_code_links":0,"syntology":null},{"paper":null,"slug":"haze-aware-attention-network-for-single-image","title":"Haze-Aware Attention Network for Single-Image Dehazing","date":"2024-07-16","arxiv_id":"2407.11505","n_code_links":0,"syntology":null},{"paper":"/paper/hierarchical-separable-video-transformer-for","slug":"hierarchical-separable-video-transformer-for","title":"Hierarchical Separable Video Transformer for Snapshot Compressive Imaging","date":"2024-07-16","arxiv_id":"2407.11946","n_code_links":1,"syntology":null},{"paper":null,"slug":"how-are-llms-mitigating-stereotyping-harms","title":"How Are LLMs Mitigating Stereotyping Harms? Learning from Search Engine Studies","date":"2024-07-16","arxiv_id":"2407.11733","n_code_links":0,"syntology":null},{"paper":null,"slug":"interpretability-in-action-exploratory","title":"Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent","date":"2024-07-16","arxiv_id":"2407.12161","n_code_links":0,"syntology":null},{"paper":"/paper/lami-detr-open-vocabulary-detection-with","slug":"lami-detr-open-vocabulary-detection-with","title":"LaMI-DETR: Open-Vocabulary Detection with Language Model Instruction","date":"2024-07-16","arxiv_id":"2407.11335","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":2,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["eternaldolphin/lami-detr"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"large-language-models-as-misleading","title":"Large Language Models as Misleading Assistants in Conversation","date":"2024-07-16","arxiv_id":"2407.11789","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-visual-language-models-are-also-good","title":"Large Visual-Language Models Are Also Good Classifiers: A Study of In-Context Multimodal Fake News Detection","date":"2024-07-16","arxiv_id":"2407.12879","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-global-and-local-features-of-power","title":"Learning Global and Local Features of Power Load Series Through Transformer and 2D-CNN: An Image-based Multi-step Forecasting Approach Incorporating Phase Space Reconstruction","date":"2024-07-16","arxiv_id":"2407.11553","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-multi-view-anomaly-detection","title":"Learning Multi-view Anomaly Detection","date":"2024-07-16","arxiv_id":"2407.11935","n_code_links":0,"syntology":null},{"paper":null,"slug":"llms-in-the-loop-part-1-expert-small-ai","title":"LLMs-in-the-loop Part-1: Expert Small AI Models for Bio-Medical Text Translation","date":"2024-07-16","arxiv_id":"2407.12126","n_code_links":0,"syntology":null},{"paper":"/paper/lofti-localization-and-factuality-transfer-to","slug":"lofti-localization-and-factuality-transfer-to","title":"LoFTI: Localization and Factuality Transfer to Indian Locales","date":"2024-07-16","arxiv_id":"2407.11833","n_code_links":1,"syntology":null},{"paper":"/paper/lora-pt-low-rank-adapting-unetr-for","slug":"lora-pt-low-rank-adapting-unetr-for","title":"LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and Vectors","date":"2024-07-16","arxiv_id":"2407.11292","n_code_links":1,"syntology":null},{"paper":null,"slug":"lrq-optimizing-post-training-quantization-for","title":"LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices","date":"2024-07-16","arxiv_id":"2407.11534","n_code_links":0,"syntology":null},{"paper":null,"slug":"mindful-rag-a-study-of-points-of-failure-in","title":"Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation","date":"2024-07-16","arxiv_id":"2407.12216","n_code_links":0,"syntology":null},{"paper":"/paper/monocular-occupancy-prediction-for-scalable","slug":"monocular-occupancy-prediction-for-scalable","title":"Monocular Occupancy Prediction for Scalable Indoor Scenes","date":"2024-07-16","arxiv_id":"2407.11730","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":7,"n_instrument":0,"unverified":2,"pointer_only":3,"phrase":"7 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; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["hongxiaoy/ISO"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/namer-non-autoregressive-modeling-for","slug":"namer-non-autoregressive-modeling-for","title":"NAMER: Non-Autoregressive Modeling for Handwritten Mathematical Expression Recognition","date":"2024-07-16","arxiv_id":"2407.11380","n_code_links":0,"syntology":null}],"record_sha256":"7400a9a5e139635245bbbcfba9964460848a8340cc5807d76354baf4bb2b9273","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}