{"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/label-smoothing/papers/58","list_of":"/method/label-smoothing","method":"Label Smoothing","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":58,"pages_in_order":144,"rows_per_page":100,"rows":[5701,5800],"of":14327,"counts":{"archive_papers_tagged":14327,"with_a_code_link":6651,"where_syntology_ran_a_sample":2259,"not_listed_spam_title":0,"listed":14327,"listed_where_code_ran":2259,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1920,"every_run_a_failure_of_syntologys_instrument":339,"listed_with_a_run_with_no_instrument_failure":1920,"listed_every_run_a_failure_of_syntologys_instrument":339,"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/label-smoothing","prev":"/method/label-smoothing/papers/57","next":"/method/label-smoothing/papers/59","papers":[{"paper":null,"slug":"unmasking-and-quantifying-racial-bias-of","title":"Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation","date":"2024-01-25","arxiv_id":"2401.13867","n_code_links":0,"syntology":null},{"paper":null,"slug":"vall-t-decoder-only-generative-transducer-for","title":"VALL-T: Decoder-Only Generative Transducer for Robust and Decoding-Controllable Text-to-Speech","date":"2024-01-25","arxiv_id":"2401.14321","n_code_links":0,"syntology":null},{"paper":"/paper/webvoyager-building-an-end-to-end-web-agent","slug":"webvoyager-building-an-end-to-end-web-agent","title":"WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models","date":"2024-01-25","arxiv_id":"2401.13919","n_code_links":2,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["minorjerry/webvoyager"],"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":"zero-shot-sequential-neuro-symbolic-reasoning","title":"Zero-shot Sequential Neuro-symbolic Reasoning for Automatically Generating Architecture Schematic Designs","date":"2024-01-25","arxiv_id":"2402.00052","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-root-causing-of-cloud-incidents","title":"Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4","date":"2024-01-24","arxiv_id":"2401.13810","n_code_links":0,"syntology":null},{"paper":"/paper/clue-guided-path-exploration-an-efficient","slug":"clue-guided-path-exploration-an-efficient","title":"Fine-Grained Stateful Knowledge Exploration: A Novel Paradigm for Integrating Knowledge Graphs with Large Language Models","date":"2024-01-24","arxiv_id":"2401.13444","n_code_links":1,"syntology":null},{"paper":"/paper/contextual-evaluating-context-sensitive-text","slug":"contextual-evaluating-context-sensitive-text","title":"ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models","date":"2024-01-24","arxiv_id":"2401.13311","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":["rohan598/contextual"],"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":"discovering-mathematical-formulas-from-data","title":"Discovering Mathematical Formulas from Data via GPT-guided Monte Carlo Tree Search","date":"2024-01-24","arxiv_id":"2401.14424","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-of-general-large-language-models","title":"Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes","date":"2024-01-24","arxiv_id":"2401.13588","n_code_links":0,"syntology":null},{"paper":"/paper/how-good-is-chatgpt-at-face-biometrics-a","slug":"how-good-is-chatgpt-at-face-biometrics-a","title":"How Good is ChatGPT at Face Biometrics? A First Look into Recognition, Soft Biometrics, and Explainability","date":"2024-01-24","arxiv_id":"2401.13641","n_code_links":1,"syntology":null},{"paper":null,"slug":"inadequacy-of-common-stochastic-neural","title":"Inadequacy of common stochastic neural networks for reliable clinical decision support","date":"2024-01-24","arxiv_id":"2401.13657","n_code_links":0,"syntology":null},{"paper":"/paper/inverse-molecular-design-with-multi","slug":"inverse-molecular-design-with-multi","title":"Graph Diffusion Transformers for Multi-Conditional Molecular Generation","date":"2024-01-24","arxiv_id":"2401.13858","n_code_links":1,"syntology":{"ran":7,"of":8,"n_ran_checked":6,"n_instrument":1,"unverified":1,"pointer_only":8,"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) · 1 unverified","official":{"repos":["liugangcode/MCD"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"language-guided-world-models-a-model-based","title":"Language-Guided World Models: A Model-Based Approach to AI Control","date":"2024-01-24","arxiv_id":"2402.01695","n_code_links":0,"syntology":null},{"paper":"/paper/learning-representations-for-clustering-via","slug":"learning-representations-for-clustering-via","title":"Learning Representations for Clustering via Partial Information Discrimination and Cross-Level Interaction","date":"2024-01-24","arxiv_id":"2401.13503","n_code_links":1,"syntology":null},{"paper":null,"slug":"research-about-the-ability-of-llm-in-the","title":"Research about the Ability of LLM in the Tamper-Detection Area","date":"2024-01-24","arxiv_id":"2401.13504","n_code_links":0,"syntology":null},{"paper":"/paper/segmamba-long-range-sequential-modeling-mamba","slug":"segmamba-long-range-sequential-modeling-mamba","title":"SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation","date":"2024-01-24","arxiv_id":"2401.13560","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ge-xing/segmamba"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"segment-any-cell-a-sam-based-auto-prompting","title":"Segment Any Cell: A SAM-based Auto-prompting Fine-tuning Framework for Nuclei Segmentation","date":"2024-01-24","arxiv_id":"2401.13220","n_code_links":0,"syntology":null},{"paper":null,"slug":"tat-llm-a-specialized-language-model-for","title":"TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data","date":"2024-01-24","arxiv_id":"2401.13223","n_code_links":0,"syntology":null},{"paper":"/paper/args-alignment-as-reward-guided-search","slug":"args-alignment-as-reward-guided-search","title":"ARGS: Alignment as Reward-Guided Search","date":"2024-01-23","arxiv_id":"2402.01694","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":4,"n_instrument":1,"unverified":0,"pointer_only":5,"phrase":"5 ran (of which 1 constructed an object rather than computing a result; 4 with no instrument failure: 3 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["deeplearning-wisc/args"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":1,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"el-vit-probing-vision-transformer-with","title":"EL-VIT: Probing Vision Transformer with Interactive Visualization","date":"2024-01-23","arxiv_id":"2401.12666","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploration-and-improvement-of-nerf-based-3d","title":"Exploration and Improvement of Nerf-based 3D Scene Editing Techniques","date":"2024-01-23","arxiv_id":"2401.12456","n_code_links":0,"syntology":null},{"paper":null,"slug":"kam-cot-knowledge-augmented-multimodal-chain","title":"KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning","date":"2024-01-23","arxiv_id":"2401.12863","n_code_links":0,"syntology":null},{"paper":"/paper/mast-video-polyp-segmentation-with-a-mixture","slug":"mast-video-polyp-segmentation-with-a-mixture","title":"MAST: Video Polyp Segmentation with a Mixture-Attention Siamese Transformer","date":"2024-01-23","arxiv_id":"2401.12439","n_code_links":1,"syntology":null},{"paper":"/paper/meta-prompting-enhancing-language-models-with","slug":"meta-prompting-enhancing-language-models-with","title":"Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding","date":"2024-01-23","arxiv_id":"2401.12954","n_code_links":1,"syntology":{"ran":5,"of":7,"n_ran_checked":5,"n_instrument":0,"unverified":2,"pointer_only":4,"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) · 2 unverified","official":{"repos":["suzgunmirac/meta-prompting"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"on-the-efficacy-of-text-based-input","title":"On the Efficacy of Text-Based Input Modalities for Action Anticipation","date":"2024-01-23","arxiv_id":"2401.12972","n_code_links":0,"syntology":null},{"paper":null,"slug":"quality-of-answers-of-generative-large","title":"Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study","date":"2024-01-23","arxiv_id":"2402.01693","n_code_links":0,"syntology":null},{"paper":null,"slug":"beta-binarized-energy-efficient-transformer","title":"BETA: Binarized Energy-Efficient Transformer Accelerator at the Edge","date":"2024-01-22","arxiv_id":"2401.11851","n_code_links":0,"syntology":null},{"paper":null,"slug":"codebook-enabled-generative-end-to-end","title":"Codebook-enabled Generative End-to-end Semantic Communication Powered by Transformer","date":"2024-01-22","arxiv_id":"2402.16868","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-in-context-learning-via-linear","slug":"enhancing-in-context-learning-via-linear","title":"Enhancing In-context Learning via Linear Probe Calibration","date":"2024-01-22","arxiv_id":"2401.12406","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"pointer_only":6,"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) · 3 unverified","official":{"repos":["mominabbass/linc"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"evaluation-of-qcnn-lstm-for-disability","title":"Evaluation of QCNN-LSTM for Disability Forecasting in Multiple Sclerosis Using Sequential Multisequence MRI","date":"2024-01-22","arxiv_id":"2401.12132","n_code_links":0,"syntology":null},{"paper":null,"slug":"friends-across-time-multi-scale-action","title":"Friends Across Time: Multi-Scale Action Segmentation Transformer for Surgical Phase Recognition","date":"2024-01-22","arxiv_id":"2401.11644","n_code_links":0,"syntology":null},{"paper":null,"slug":"investigating-large-language-models-for","title":"Investigating Large Language Models for Financial Causality Detection in Multilingual Setup","date":"2024-01-22","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/lkformer-large-kernel-transformer-for","slug":"lkformer-large-kernel-transformer-for","title":"LKFormer: Large Kernel Transformer for Infrared Image Super-Resolution","date":"2024-01-22","arxiv_id":"2401.11859","n_code_links":1,"syntology":null},{"paper":null,"slug":"mssvt-mixed-scale-sparse-voxel-transformer","title":"MsSVT++: Mixed-scale Sparse Voxel Transformer with Center Voting for 3D Object Detection","date":"2024-01-22","arxiv_id":"2401.11718","n_code_links":0,"syntology":null},{"paper":"/paper/ondev-lct-on-device-lightweight-convolutional","slug":"ondev-lct-on-device-lightweight-convolutional","title":"OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning","date":"2024-01-22","arxiv_id":"2401.11652","n_code_links":0,"syntology":null},{"paper":null,"slug":"p2dt-mitigating-forgetting-in-task","title":"P2DT: Mitigating Forgetting in task-incremental Learning with progressive prompt Decision Transformer","date":"2024-01-22","arxiv_id":"2401.11666","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-cross-attention-for-infrared-and","title":"ATFusion: An Alternate Cross-Attention Transformer Network for Infrared and Visible Image Fusion","date":"2024-01-22","arxiv_id":"2401.11675","n_code_links":0,"syntology":null},{"paper":null,"slug":"revolutionizing-finance-with-llms-an-overview","title":"Revolutionizing Finance with LLMs: An Overview of Applications and Insights","date":"2024-01-22","arxiv_id":"2401.11641","n_code_links":0,"syntology":null},{"paper":"/paper/speak-it-out-solving-symbol-related-problems","slug":"speak-it-out-solving-symbol-related-problems","title":"Speak It Out: Solving Symbol-Related Problems with Symbol-to-Language Conversion for Language Models","date":"2024-01-22","arxiv_id":"2401.11725","n_code_links":1,"syntology":null},{"paper":"/paper/superclue-math6-graded-multi-step-math","slug":"superclue-math6-graded-multi-step-math","title":"SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese","date":"2024-01-22","arxiv_id":"2401.11819","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-bigger-the-better-rethinking-the","title":"Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting","date":"2024-01-22","arxiv_id":"2401.11929","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-augmentation-training-makes","slug":"adversarial-augmentation-training-makes","title":"Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts","date":"2024-01-21","arxiv_id":"2401.11406","n_code_links":1,"syntology":null},{"paper":null,"slug":"attentionlego-an-open-source-building-block","title":"AttentionLego: An Open-Source Building Block For Spatially-Scalable Large Language Model Accelerator With Processing-In-Memory Technology","date":"2024-01-21","arxiv_id":"2401.11459","n_code_links":0,"syntology":null},{"paper":null,"slug":"epilepsy-seizure-detection-and-prediction","title":"Epilepsy Seizure Detection and Prediction using an Approximate Spiking Convolutional Transformer","date":"2024-01-21","arxiv_id":"2402.09424","n_code_links":0,"syntology":null},{"paper":null,"slug":"freely-long-thinking-transformer-frailt","title":"Freely Long-Thinking Transformer (FraiLT)","date":"2024-01-21","arxiv_id":"2401.11626","n_code_links":0,"syntology":null},{"paper":"/paper/language-models-as-hierarchy-encoders","slug":"language-models-as-hierarchy-encoders","title":"Language Models as Hierarchy Encoders","date":"2024-01-21","arxiv_id":"2401.11374","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":7,"n_instrument":0,"unverified":2,"pointer_only":0,"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":["krr-oxford/hierarchytransformers"],"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":null,"slug":"llmra-multi-modal-large-language-model-based","title":"LLMRA: Multi-modal Large Language Model based Restoration Assistant","date":"2024-01-21","arxiv_id":"2401.11401","n_code_links":0,"syntology":null},{"paper":"/paper/prolex-a-benchmark-for-language-proficiency","slug":"prolex-a-benchmark-for-language-proficiency","title":"ProLex: A Benchmark for Language Proficiency-oriented Lexical Substitution","date":"2024-01-21","arxiv_id":"2401.11356","n_code_links":1,"syntology":null},{"paper":"/paper/scalable-high-resolution-pixel-space-image","slug":"scalable-high-resolution-pixel-space-image","title":"Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers","date":"2024-01-21","arxiv_id":"2401.11605","n_code_links":1,"syntology":null},{"paper":null,"slug":"training-microrobots-to-swim-by-a-large","title":"Training microrobots to swim by a large language model","date":"2024-01-21","arxiv_id":"2402.00044","n_code_links":0,"syntology":null},{"paper":"/paper/badchain-backdoor-chain-of-thought-prompting","slug":"badchain-backdoor-chain-of-thought-prompting","title":"BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models","date":"2024-01-20","arxiv_id":"2401.12242","n_code_links":1,"syntology":{"ran":13,"of":15,"n_ran_checked":13,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["django-jiang/badchain"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/denguenet-dengue-prediction-using","slug":"denguenet-dengue-prediction-using","title":"DengueNet: Dengue Prediction using Spatiotemporal Satellite Imagery for Resource-Limited Countries","date":"2024-01-20","arxiv_id":"2401.11114","n_code_links":1,"syntology":null},{"paper":"/paper/drop-your-decoder-pre-training-with-bag-of","slug":"drop-your-decoder-pre-training-with-bag-of","title":"Drop your Decoder: Pre-training with Bag-of-Word Prediction for Dense Passage Retrieval","date":"2024-01-20","arxiv_id":"2401.11248","n_code_links":3,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"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) · 0 unverified","official":{"repos":["ma787639046/bowdpr"],"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":["listed","official"]}}},{"paper":null,"slug":"enhancing-large-language-models-for-clinical","title":"Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines","date":"2024-01-20","arxiv_id":"2401.11120","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-and-enhancing-large-language","title":"Evaluating and Enhancing Large Language Models Performance in Domain-specific Medicine: Osteoarthritis Management with DocOA","date":"2024-01-20","arxiv_id":"2401.12998","n_code_links":0,"syntology":null},{"paper":"/paper/gaussian-adaptive-attention-is-all-you-need","slug":"gaussian-adaptive-attention-is-all-you-need","title":"Density Adaptive Attention is All You Need: Robust Parameter-Efficient Fine-Tuning Across Multiple Modalities","date":"2024-01-20","arxiv_id":"2401.11143","n_code_links":2,"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, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["gioannides/gaussian-adaptive-attention"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/inducing-high-energy-latency-of-large-vision","slug":"inducing-high-energy-latency-of-large-vision","title":"Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images","date":"2024-01-20","arxiv_id":"2401.11170","n_code_links":1,"syntology":{"ran":5,"of":7,"n_ran_checked":0,"n_instrument":5,"unverified":2,"pointer_only":7,"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) · 2 unverified","official":{"repos":["kuofenggao/verbose_images"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/lmuformer-low-complexity-yet-powerful-spiking","slug":"lmuformer-low-complexity-yet-powerful-spiking","title":"LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units","date":"2024-01-20","arxiv_id":"2402.04882","n_code_links":1,"syntology":{"ran":9,"of":12,"n_ran_checked":9,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"9 ran (of which 1 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) · 3 unverified","official":{"repos":["zeyuliu1037/lmuformer"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":1,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/uncertainty-aware-bridge-based-mobile-former","slug":"uncertainty-aware-bridge-based-mobile-former","title":"Uncertainty-aware Bridge based Mobile-Former Network for Event-based Pattern Recognition","date":"2024-01-20","arxiv_id":"2401.11123","n_code_links":1,"syntology":null},{"paper":null,"slug":"unfair-tos-an-automated-approach-using","title":"Unfair TOS: An Automated Approach using Customized BERT","date":"2024-01-20","arxiv_id":"2401.11207","n_code_links":0,"syntology":null},{"paper":"/paper/aat-adapting-audio-transformer-for-various","slug":"aat-adapting-audio-transformer-for-various","title":"AAT: Adapting Audio Transformer for Various Acoustics Recognition Tasks","date":"2024-01-19","arxiv_id":"2401.10544","n_code_links":1,"syntology":null},{"paper":"/paper/attentive-fusion-a-transformer-based-approach","slug":"attentive-fusion-a-transformer-based-approach","title":"Attentive Fusion: A Transformer-based Approach to Multimodal Hate Speech Detection","date":"2024-01-19","arxiv_id":"2401.10653","n_code_links":2,"syntology":null},{"paper":"/paper/deeprli-a-multi-objective-framework-for","slug":"deeprli-a-multi-objective-framework-for","title":"DeepRLI: A Multi-objective Framework for Universal Protein--Ligand Interaction Prediction","date":"2024-01-19","arxiv_id":"2401.10806","n_code_links":1,"syntology":null},{"paper":"/paper/m2ort-many-to-one-regression-transformer-for","slug":"m2ort-many-to-one-regression-transformer-for","title":"M2ORT: Many-To-One Regression Transformer for Spatial Transcriptomics Prediction from Histopathology Images","date":"2024-01-19","arxiv_id":"2401.10608","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"pointer_only":3,"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) · 2 unverified","official":{"repos":["dootmaan/m2ort"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"mdgnn-multi-relational-dynamic-graph-neural","title":"MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction","date":"2024-01-19","arxiv_id":"2402.06633","n_code_links":0,"syntology":null},{"paper":"/paper/mementos-a-comprehensive-benchmark-for","slug":"mementos-a-comprehensive-benchmark-for","title":"Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences","date":"2024-01-19","arxiv_id":"2401.10529","n_code_links":1,"syntology":null},{"paper":"/paper/mining-experimental-data-from-materials","slug":"mining-experimental-data-from-materials","title":"Mining experimental data from Materials Science literature with Large Language Models: an evaluation study","date":"2024-01-19","arxiv_id":"2401.11052","n_code_links":1,"syntology":null},{"paper":null,"slug":"speech-swin-transformer-exploring-a","title":"Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition","date":"2024-01-19","arxiv_id":"2401.10536","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-video-transformers-via","title":"Understanding Video Transformers via Universal Concept Discovery","date":"2024-01-19","arxiv_id":"2401.10831","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-empirical-study-on-the-impact-of-1","title":"An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement","date":"2024-01-18","arxiv_id":"2401.09686","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-reference-based-metrics-analyzing","title":"Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation","date":"2024-01-18","arxiv_id":"2401.10186","n_code_links":0,"syntology":null},{"paper":"/paper/blenda-domain-adaptive-object-detection","slug":"blenda-domain-adaptive-object-detection","title":"BlenDA: Domain Adaptive Object Detection through diffusion-based blending","date":"2024-01-18","arxiv_id":"2401.09921","n_code_links":1,"syntology":null},{"paper":"/paper/chatqa-building-gpt-4-level-conversational-qa","slug":"chatqa-building-gpt-4-level-conversational-qa","title":"ChatQA: Surpassing GPT-4 on Conversational QA and RAG","date":"2024-01-18","arxiv_id":"2401.10225","n_code_links":0,"syntology":null},{"paper":null,"slug":"controllable-decontextualization-of-yes-no","title":"Controllable Decontextualization of Yes/No Question and Answers into Factual Statements","date":"2024-01-18","arxiv_id":"2401.09775","n_code_links":0,"syntology":null},{"paper":null,"slug":"curriculum-recommendations-using-transformer","title":"Curriculum Recommendations Using Transformer Base Model with InfoNCE Loss And Language Switching Method","date":"2024-01-18","arxiv_id":"2401.09699","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-general-intelligence-via-gated","title":"Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies","date":"2024-01-18","arxiv_id":"2401.10348","n_code_links":0,"syntology":null},{"paper":null,"slug":"gender-bias-in-machine-translation-and-the","title":"Gender Bias in Machine Translation and The Era of Large Language Models","date":"2024-01-18","arxiv_id":"2401.10016","n_code_links":0,"syntology":null},{"paper":"/paper/r-judge-benchmarking-safety-risk-awareness","slug":"r-judge-benchmarking-safety-risk-awareness","title":"R-Judge: Benchmarking Safety Risk Awareness for LLM Agents","date":"2024-01-18","arxiv_id":"2401.10019","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":["lordog/r-judge"],"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":"reconstructing-the-invisible-video-frame","title":"Reconstructing the Invisible: Video Frame Restoration through Siamese Masked Conditional Variational Autoencoder","date":"2024-01-18","arxiv_id":"2401.10402","n_code_links":0,"syntology":null},{"paper":"/paper/self-rewarding-language-models","slug":"self-rewarding-language-models","title":"Self-Rewarding Language Models","date":"2024-01-18","arxiv_id":"2401.10020","n_code_links":3,"syntology":{"ran":6,"of":11,"n_ran_checked":5,"n_instrument":1,"unverified":5,"pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 2 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","official":null}},{"paper":"/paper/towards-principled-graph-transformers","slug":"towards-principled-graph-transformers","title":"Towards Principled Graph Transformers","date":"2024-01-18","arxiv_id":"2401.10119","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":["luis-mueller/towards-principled-gts"],"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":"attackeval-how-to-evaluate-the-effectiveness","title":"AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models","date":"2024-01-17","arxiv_id":"2401.09002","n_code_links":0,"syntology":null},{"paper":"/paper/augmenting-math-word-problems-via-iterative","slug":"augmenting-math-word-problems-via-iterative","title":"Augmenting Math Word Problems via Iterative Question Composing","date":"2024-01-17","arxiv_id":"2401.09003","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"pointer_only":4,"phrase":"4 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; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["iiis-ai/iterativequestioncomposing"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/beno-boundary-embedded-neural-operators-for","slug":"beno-boundary-embedded-neural-operators-for","title":"BENO: Boundary-embedded Neural Operators for Elliptic PDEs","date":"2024-01-17","arxiv_id":"2401.09323","n_code_links":1,"syntology":{"ran":5,"of":9,"n_ran_checked":4,"n_instrument":1,"unverified":4,"pointer_only":0,"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) · 4 unverified","official":{"repos":["ai4science-westlakeu/beno"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/bridging-research-and-readers-a-multi-modal","slug":"bridging-research-and-readers-a-multi-modal","title":"Bridging Research and Readers: A Multi-Modal Automated Academic Papers Interpretation System","date":"2024-01-17","arxiv_id":"2401.09150","n_code_links":1,"syntology":null},{"paper":"/paper/coco-is-all-you-need-for-visual-instruction","slug":"coco-is-all-you-need-for-visual-instruction","title":"COCO is \"ALL'' You Need for Visual Instruction Fine-tuning","date":"2024-01-17","arxiv_id":"2401.08968","n_code_links":0,"syntology":null},{"paper":"/paper/deciphering-textual-authenticity-a","slug":"deciphering-textual-authenticity-a","title":"Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Text","date":"2024-01-17","arxiv_id":"2401.09407","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamic-relation-transformer-for-contextual","title":"Dynamic Relation Transformer for Contextual Text Block Detection","date":"2024-01-17","arxiv_id":"2401.09232","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-generative-adversarial-networks","slug":"efficient-generative-adversarial-networks","title":"Efficient generative adversarial networks using linear additive-attention Transformers","date":"2024-01-17","arxiv_id":"2401.09596","n_code_links":2,"syntology":null},{"paper":null,"slug":"from-user-surveys-to-telemetry-driven-agents","title":"From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions","date":"2024-01-17","arxiv_id":"2401.08960","n_code_links":0,"syntology":null},{"paper":null,"slug":"impact-of-large-language-model-assistance-on","title":"Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study","date":"2024-01-17","arxiv_id":"2401.09637","n_code_links":0,"syntology":null},{"paper":"/paper/mshyper-multi-scale-hypergraph-transformer","slug":"mshyper-multi-scale-hypergraph-transformer","title":"MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting","date":"2024-01-17","arxiv_id":"2401.09261","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":0,"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":["shangzongjiang/MSHyper"],"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":"siamese-meets-diffusion-network-smdnet-for","title":"Siamese Meets Diffusion Network: SMDNet for Enhanced Change Detection in High-Resolution RS Imagery","date":"2024-01-17","arxiv_id":"2401.09325","n_code_links":0,"syntology":null},{"paper":"/paper/stuck-in-the-quicksand-of-numeracy-far-from","slug":"stuck-in-the-quicksand-of-numeracy-far-from","title":"Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided Interventions","date":"2024-01-17","arxiv_id":"2401.09395","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":0,"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":["declare-lab/llm-reasoningtest"],"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":"swbt-similarity-weighted-behavior-transformer","title":"Learning from Imperfect Demonstrations with Self-Supervision for Robotic Manipulation","date":"2024-01-17","arxiv_id":"2401.08957","n_code_links":0,"syntology":null},{"paper":"/paper/symtc-a-symbiotic-transformer-cnn-net-for","slug":"symtc-a-symbiotic-transformer-cnn-net-for","title":"SymTC: A Symbiotic Transformer-CNN Net for Instance Segmentation of Lumbar Spine MRI","date":"2024-01-17","arxiv_id":"2401.09627","n_code_links":1,"syntology":null},{"paper":"/paper/trapped-in-texture-bias-a-large-scale","slug":"trapped-in-texture-bias-a-large-scale","title":"Trapped in texture bias? A large scale comparison of deep instance segmentation","date":"2024-01-17","arxiv_id":"2401.09109","n_code_links":1,"syntology":null},{"paper":null,"slug":"b-cos-aligned-transformers-learn-human","title":"B-Cos Aligned Transformers Learn Human-Interpretable Features","date":"2024-01-16","arxiv_id":"2401.08868","n_code_links":0,"syntology":null},{"paper":"/paper/code-generation-with-alphacodium-from-prompt","slug":"code-generation-with-alphacodium-from-prompt","title":"Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering","date":"2024-01-16","arxiv_id":"2401.08500","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"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) · 0 unverified","official":{"repos":["codium-ai/alphacodium"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/completely-occluded-and-dense-object-instance","slug":"completely-occluded-and-dense-object-instance","title":"OBSeg: Accurate and Fast Instance Segmentation Framework Using Segmentation Foundation Models with Oriented Bounding Box Prompts","date":"2024-01-16","arxiv_id":"2401.08174","n_code_links":1,"syntology":null}],"record_sha256":"c7e7abe3298c3b1634baee7c727d10a50f9d1d90b29f8309bd724ce1c14bb145","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}