{"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/182","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":182,"pages_in_order":375,"rows_per_page":100,"rows":[18101,18200],"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/181","next":"/method/softmax/papers/183","papers":[{"paper":null,"slug":"llamas-know-what-gpts-don-t-show-surrogate","title":"Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation","date":"2023-11-15","arxiv_id":"2311.08877","n_code_links":0,"syntology":null},{"paper":null,"slug":"loke-linked-open-knowledge-extraction-for","title":"LOKE: Linked Open Knowledge Extraction for Automated Knowledge Graph Construction","date":"2023-11-15","arxiv_id":"2311.09366","n_code_links":0,"syntology":null},{"paper":"/paper/mela-multilingual-evaluation-of-linguistic","slug":"mela-multilingual-evaluation-of-linguistic","title":"MELA: Multilingual Evaluation of Linguistic Acceptability","date":"2023-11-15","arxiv_id":"2311.09033","n_code_links":1,"syntology":null},{"paper":null,"slug":"memory-augmented-language-models-through","title":"Memory Augmented Language Models through Mixture of Word Experts","date":"2023-11-15","arxiv_id":"2311.10768","n_code_links":0,"syntology":null},{"paper":"/paper/progressive-feedback-enhanced-transformer-for","slug":"progressive-feedback-enhanced-transformer-for","title":"Progressive Feedback-Enhanced Transformer for Image Forgery Localization","date":"2023-11-15","arxiv_id":"2311.08910","n_code_links":1,"syntology":null},{"paper":"/paper/safer-instruct-aligning-language-models-with","slug":"safer-instruct-aligning-language-models-with","title":"Safer-Instruct: Aligning Language Models with Automated Preference Data","date":"2023-11-15","arxiv_id":"2311.08685","n_code_links":1,"syntology":null},{"paper":null,"slug":"sparsespikformer-a-co-design-framework-for","title":"SparseSpikformer: A Co-Design Framework for Token and Weight Pruning in Spiking Transformer","date":"2023-11-15","arxiv_id":"2311.08806","n_code_links":0,"syntology":null},{"paper":"/paper/target-oriented-domain-adaptation-for","slug":"target-oriented-domain-adaptation-for","title":"Texture and Noise Dual Adaptation for Infrared Image Super-Resolution","date":"2023-11-15","arxiv_id":"2311.08816","n_code_links":1,"syntology":null},{"paper":"/paper/token-prediction-as-implicit-classification","slug":"token-prediction-as-implicit-classification","title":"Token Prediction as Implicit Classification to Identify LLM-Generated Text","date":"2023-11-15","arxiv_id":"2311.08723","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["markchenyutian/t5-sentinel-public"],"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":"/paper/tooltalk-evaluating-tool-usage-in-a","slug":"tooltalk-evaluating-tool-usage-in-a","title":"ToolTalk: Evaluating Tool-Usage in a Conversational Setting","date":"2023-11-15","arxiv_id":"2311.10775","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":null}},{"paper":"/paper/we-demand-justice-towards-grounding-political","slug":"we-demand-justice-towards-grounding-political","title":"\"We Demand Justice!\": Towards Social Context Grounding of Political Texts","date":"2023-11-15","arxiv_id":"2311.09106","n_code_links":1,"syntology":null},{"paper":null,"slug":"x-eval-generalizable-multi-aspect-text","title":"X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects","date":"2023-11-15","arxiv_id":"2311.08788","n_code_links":0,"syntology":null},{"paper":"/paper/xplainllm-a-qa-explanation-dataset-for","slug":"xplainllm-a-qa-explanation-dataset-for","title":"XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMs","date":"2023-11-15","arxiv_id":"2311.08614","n_code_links":1,"syntology":null},{"paper":"/paper/a-survey-on-language-models-for-code","slug":"a-survey-on-language-models-for-code","title":"Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code","date":"2023-11-14","arxiv_id":"2311.07989","n_code_links":1,"syntology":null},{"paper":"/paper/a-wolf-in-sheep-s-clothing-generalized-nested","slug":"a-wolf-in-sheep-s-clothing-generalized-nested","title":"A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily","date":"2023-11-14","arxiv_id":"2311.08268","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":7,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["NJUNLP/ReNeLLM"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"act-vit-a-representationally-robust-attention","title":"SkelVIT: Consensus of Vision Transformers for a Lightweight Skeleton-Based Action Recognition System","date":"2023-11-14","arxiv_id":"2311.08094","n_code_links":0,"syntology":null},{"paper":null,"slug":"artemis-using-gans-with-multiple","title":"ARTEMIS: Using GANs with Multiple Discriminators to Generate Art","date":"2023-11-14","arxiv_id":"2311.08278","n_code_links":0,"syntology":null},{"paper":"/paper/artificial-text-boundary-detection-with","slug":"artificial-text-boundary-detection-with","title":"AI-generated text boundary detection with RoFT","date":"2023-11-14","arxiv_id":"2311.08349","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":["silversolver/ai_boundary_detection"],"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/automated-title-and-abstract-screening-for","slug":"automated-title-and-abstract-screening-for","title":"Automated title and abstract screening for scoping reviews using the GPT-4 Large Language Model","date":"2023-11-14","arxiv_id":"2311.07918","n_code_links":1,"syntology":null},{"paper":null,"slug":"comparing-humans-gpt-4-and-gpt-4v-on","title":"Comparing Humans, GPT-4, and GPT-4V On Abstraction and Reasoning Tasks","date":"2023-11-14","arxiv_id":"2311.09247","n_code_links":0,"syntology":null},{"paper":"/paper/contrastive-learning-for-multi-object","slug":"contrastive-learning-for-multi-object","title":"Contrastive Learning for Multi-Object Tracking with Transformers","date":"2023-11-14","arxiv_id":"2311.08043","n_code_links":1,"syntology":null},{"paper":null,"slug":"cpopqa-ranking-cultural-concept-popularity-by","title":"CPopQA: Ranking Cultural Concept Popularity by LLMs","date":"2023-11-14","arxiv_id":"2311.07897","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-dataset-domain-adaptation-for-the","title":"Cross-dataset domain adaptation for the classification COVID-19 using chest computed tomography images","date":"2023-11-14","arxiv_id":"2311.08524","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-channel-prototype-network-for-few-shot","title":"Dual-channel Prototype Network for few-shot Classification of Pathological Images","date":"2023-11-14","arxiv_id":"2311.07871","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-llms-on-document-based-qa-exact","title":"Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset","date":"2023-11-14","arxiv_id":"2311.07878","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-semi-supervised-hierarchical","slug":"exploring-semi-supervised-hierarchical","title":"Exploring Semi-supervised Hierarchical Stacked Encoder for Legal Judgement Prediction","date":"2023-11-14","arxiv_id":"2311.08103","n_code_links":1,"syntology":null},{"paper":"/paper/fair-abstractive-summarization-of-diverse","slug":"fair-abstractive-summarization-of-diverse","title":"Fair Abstractive Summarization of Diverse Perspectives","date":"2023-11-14","arxiv_id":"2311.07884","n_code_links":1,"syntology":null},{"paper":"/paper/gmtr-graph-matching-transformers","slug":"gmtr-graph-matching-transformers","title":"GMTR: Graph Matching Transformers","date":"2023-11-14","arxiv_id":"2311.08141","n_code_links":1,"syntology":null},{"paper":null,"slug":"how-good-are-large-language-models-on-african","title":"How good are Large Language Models on African Languages?","date":"2023-11-14","arxiv_id":"2311.07978","n_code_links":0,"syntology":null},{"paper":null,"slug":"investigating-the-encoding-of-words-in-bert-s","title":"Investigating the Encoding of Words in BERT's Neurons using Feature Textualization","date":"2023-11-14","arxiv_id":"2311.08240","n_code_links":0,"syntology":null},{"paper":"/paper/language-models-are-better-bug-detector","slug":"language-models-are-better-bug-detector","title":"Language Models are Better Bug Detector Through Code-Pair Classification","date":"2023-11-14","arxiv_id":"2311.07957","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-language-model-driven-classroom","title":"Large Language Model-Driven Classroom Flipping: Empowering Student-Centric Peer Questioning with Flipped Interaction","date":"2023-11-14","arxiv_id":"2311.14708","n_code_links":0,"syntology":null},{"paper":"/paper/magic-benchmarking-large-language-model","slug":"magic-benchmarking-large-language-model","title":"MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration","date":"2023-11-14","arxiv_id":"2311.08562","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":["cathyxl/magic"],"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/memory-efficient-stochastic-methods-for","slug":"memory-efficient-stochastic-methods-for","title":"Memory-efficient Stochastic methods for Memory-based Transformers","date":"2023-11-14","arxiv_id":"2311.08123","n_code_links":1,"syntology":null},{"paper":null,"slug":"performance-of-machine-learning","title":"Performance of Machine Learning Classification in Mammography Images using BI-RADS","date":"2023-11-14","arxiv_id":"2311.08493","n_code_links":0,"syntology":null},{"paper":null,"slug":"rotation-agnostic-image-representation","title":"Rotation-Agnostic Image Representation Learning for Digital Pathology","date":"2023-11-14","arxiv_id":"2311.08359","n_code_links":0,"syntology":null},{"paper":"/paper/secure-transformer-inference","slug":"secure-transformer-inference","title":"Secure Transformer Inference Protocol","date":"2023-11-14","arxiv_id":"2312.00025","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":1,"n_instrument":3,"unverified":0,"pointer_only":1,"phrase":"4 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yuanmu97/secure-transformer-inference"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"simplesafetytests-a-test-suite-for","title":"SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models","date":"2023-11-14","arxiv_id":"2311.08370","n_code_links":0,"syntology":null},{"paper":"/paper/spot-a-natural-language-interface-for","slug":"spot-a-natural-language-interface-for","title":"Spot: A Natural Language Interface for Geospatial Searches in OSM","date":"2023-11-14","arxiv_id":"2311.08093","n_code_links":1,"syntology":null},{"paper":null,"slug":"ut5-pretraining-non-autoregressive-t5-with","title":"UT5: Pretraining Non autoregressive T5 with unrolled denoising","date":"2023-11-14","arxiv_id":"2311.08552","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-benchmark-to-understand-the-role-of","title":"A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases","date":"2023-11-13","arxiv_id":"2311.07509","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-large-deviations-perspective-on-policy","title":"A Large Deviations Perspective on Policy Gradient Algorithms","date":"2023-11-13","arxiv_id":"2311.07411","n_code_links":0,"syntology":null},{"paper":"/paper/assessing-logical-puzzle-solving-in-large","slug":"assessing-logical-puzzle-solving-in-large","title":"Assessing Logical Puzzle Solving in Large Language Models: Insights from a Minesweeper Case Study","date":"2023-11-13","arxiv_id":"2311.07387","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["yinghao-li/minesweeper-for-llm"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"cross-axis-transformer-with-2d-rotary","title":"Cross-Axis Transformer with 3D Rotary Positional Embeddings","date":"2023-11-13","arxiv_id":"2311.07184","n_code_links":0,"syntology":null},{"paper":"/paper/do-large-language-models-and-humans-have","slug":"do-large-language-models-and-humans-have","title":"Do large language models and humans have similar behaviors in causal inference with script knowledge?","date":"2023-11-13","arxiv_id":"2311.07311","n_code_links":1,"syntology":null},{"paper":"/paper/fovea-transformer-efficient-long-context","slug":"fovea-transformer-efficient-long-context","title":"Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse Attention","date":"2023-11-13","arxiv_id":"2311.07102","n_code_links":1,"syntology":null},{"paper":"/paper/in-context-learning-generalizes-but-not","slug":"in-context-learning-generalizes-but-not","title":"In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax","date":"2023-11-13","arxiv_id":"2311.07811","n_code_links":1,"syntology":null},{"paper":"/paper/interaction-is-all-you-need-a-study-of-robots","slug":"interaction-is-all-you-need-a-study-of-robots","title":"Interaction is all You Need? A Study of Robots Ability to Understand and Execute","date":"2023-11-13","arxiv_id":"2311.07150","n_code_links":1,"syntology":null},{"paper":"/paper/it-s-not-easy-being-wrong-evaluating-process","slug":"it-s-not-easy-being-wrong-evaluating-process","title":"It's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning","date":"2023-11-13","arxiv_id":"2311.07532","n_code_links":1,"syntology":null},{"paper":null,"slug":"language-grounded-qformer-for-efficient","title":"Semantically Grounded QFormer for Efficient Vision Language Understanding","date":"2023-11-13","arxiv_id":"2311.07449","n_code_links":0,"syntology":null},{"paper":null,"slug":"language-model-in-the-loop-data-optimal","title":"Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games","date":"2023-11-13","arxiv_id":"2311.07687","n_code_links":0,"syntology":null},{"paper":null,"slug":"lm-polygraph-uncertainty-estimation-for","title":"LM-Polygraph: Uncertainty Estimation for Language Models","date":"2023-11-13","arxiv_id":"2311.07383","n_code_links":0,"syntology":null},{"paper":null,"slug":"megaverse-benchmarking-large-language-models","title":"MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks","date":"2023-11-13","arxiv_id":"2311.07463","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-the-truthfulness-of-surprisingly-likely","title":"On The Truthfulness of 'Surprisingly Likely' Responses of Large Language Models","date":"2023-11-13","arxiv_id":"2311.07692","n_code_links":0,"syntology":null},{"paper":null,"slug":"speech-based-slot-filling-using-large","title":"Speech-based Slot Filling using Large Language Models","date":"2023-11-13","arxiv_id":"2311.07418","n_code_links":0,"syntology":null},{"paper":"/paper/steer-unified-style-transfer-with-expert","slug":"steer-unified-style-transfer-with-expert","title":"STEER: Unified Style Transfer with Expert Reinforcement","date":"2023-11-13","arxiv_id":"2311.07167","n_code_links":1,"syntology":null},{"paper":null,"slug":"teach-me-with-a-whisper-enhancing-large","title":"Teach me with a Whisper: Enhancing Large Language Models for Analyzing Spoken Transcripts using Speech Embeddings","date":"2023-11-13","arxiv_id":"2311.07014","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-impact-of-large-language-models-on","title":"The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4","date":"2023-11-13","arxiv_id":"2311.07361","n_code_links":0,"syntology":null},{"paper":null,"slug":"ttmfn-two-stream-transformer-based-multimodal","title":"TTMFN: Two-stream Transformer-based Multimodal Fusion Network for Survival Prediction","date":"2023-11-13","arxiv_id":"2311.07033","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-musical-object-discovery-from","slug":"unsupervised-musical-object-discovery-from","title":"Unsupervised Musical Object Discovery from Audio","date":"2023-11-13","arxiv_id":"2311.07534","n_code_links":1,"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":["arahosu/musicslots"],"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/veritymath-advancing-mathematical-reasoning","slug":"veritymath-advancing-mathematical-reasoning","title":"VerityMath: Advancing Mathematical Reasoning by Self-Verification Through Unit Consistency","date":"2023-11-13","arxiv_id":"2311.07172","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":["vernontoh/veritymath"],"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":"controllable-topic-focused-abstractive","title":"Controllable Topic-Focused Abstractive Summarization","date":"2023-11-12","arxiv_id":"2311.06724","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-and-correcting-hate-speech-in","title":"Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model","date":"2023-11-12","arxiv_id":"2311.06737","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-of-gpt-4-for-chest-x-ray","title":"Evaluation of GPT-4 for chest X-ray impression generation: A reader study on performance and perception","date":"2023-11-12","arxiv_id":"2311.06815","n_code_links":0,"syntology":null},{"paper":"/paper/flames-benchmarking-value-alignment-of","slug":"flames-benchmarking-value-alignment-of","title":"Flames: Benchmarking Value Alignment of LLMs in Chinese","date":"2023-11-12","arxiv_id":"2311.06899","n_code_links":1,"syntology":null},{"paper":null,"slug":"from-complex-to-simple-unraveling-the","title":"From Complex to Simple: Unraveling the Cognitive Tree for Reasoning with Small Language Models","date":"2023-11-12","arxiv_id":"2311.06754","n_code_links":0,"syntology":null},{"paper":null,"slug":"giellm-japanese-general-information","title":"GIELLM: Japanese General Information Extraction Large Language Model Utilizing Mutual Reinforcement Effect","date":"2023-11-12","arxiv_id":"2311.06838","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-understanding-of-math","title":"Large Language Models' Understanding of Math: Source Criticism and Extrapolation","date":"2023-11-12","arxiv_id":"2311.07618","n_code_links":0,"syntology":null},{"paper":null,"slug":"retrieval-and-generative-approaches-for-a","title":"Retrieval and Generative Approaches for a Pregnancy Chatbot in Nepali with Stemmed and Non-Stemmed Data : A Comparative Study","date":"2023-11-12","arxiv_id":"2311.06898","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-explain-teaching-large-language-models","title":"Large Language Models are In-context Teachers for Knowledge Reasoning","date":"2023-11-12","arxiv_id":"2311.06985","n_code_links":0,"syntology":null},{"paper":null,"slug":"tsvit-a-time-series-vision-transformer-for","title":"TSViT: A Time Series Vision Transformer for Fault Diagnosis","date":"2023-11-12","arxiv_id":"2311.06916","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-stream-scene-understanding-on-graph","title":"Two Stream Scene Understanding on Graph Embedding","date":"2023-11-12","arxiv_id":"2311.06746","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-fine-tuning-using-generated","slug":"adversarial-fine-tuning-using-generated","title":"Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance","date":"2023-11-11","arxiv_id":"2311.06480","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 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) · 0 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["kaen2891/adversarial_fine-tuning_using_generated_respiratory_sound"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/cvthead-one-shot-controllable-head-avatar","slug":"cvthead-one-shot-controllable-head-avatar","title":"CVTHead: One-shot Controllable Head Avatar with Vertex-feature Transformer","date":"2023-11-11","arxiv_id":"2311.06443","n_code_links":1,"syntology":{"ran":5,"of":6,"n_ran_checked":2,"n_instrument":3,"unverified":1,"pointer_only":6,"phrase":"5 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; 3 where Syntology's instrument failed) · 1 unverified","official":{"repos":["howiema/cvthead"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"intentional-biases-in-llm-responses","title":"Intentional Biases in LLM Responses","date":"2023-11-11","arxiv_id":"2311.07611","n_code_links":0,"syntology":null},{"paper":"/paper/online-continual-learning-via-logit-adjusted","slug":"online-continual-learning-via-logit-adjusted","title":"Online Continual Learning via Logit Adjusted Softmax","date":"2023-11-11","arxiv_id":"2311.06460","n_code_links":1,"syntology":null},{"paper":null,"slug":"sparse-attention-based-neural-networks-for","title":"Sparse Attention-Based Neural Networks for Code Classification","date":"2023-11-11","arxiv_id":"2311.06575","n_code_links":0,"syntology":null},{"paper":null,"slug":"argumentation-element-annotation-modeling","title":"Argumentation Element Annotation Modeling using XLNet","date":"2023-11-10","arxiv_id":"2311.06239","n_code_links":0,"syntology":null},{"paper":"/paper/automatic-report-generation-for","slug":"automatic-report-generation-for","title":"Automatic Report Generation for Histopathology images using pre-trained Vision Transformers","date":"2023-11-10","arxiv_id":"2311.06176","n_code_links":1,"syntology":null},{"paper":"/paper/data-contamination-quiz-a-tool-to-detect-and","slug":"data-contamination-quiz-a-tool-to-detect-and","title":"Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models","date":"2023-11-10","arxiv_id":"2311.06233","n_code_links":2,"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":["shahriargolchin/dcq"],"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/dual-input-stream-transformer-for-eye","slug":"dual-input-stream-transformer-for-eye","title":"Dual input stream transformer for vertical drift correction in eye-tracking reading data","date":"2023-11-10","arxiv_id":"2311.06095","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhancing-rock-image-segmentation-in-digital","title":"Enhancing Rock Image Segmentation in Digital Rock Physics: A Fusion of Generative AI and State-of-the-Art Neural Networks","date":"2023-11-10","arxiv_id":"2311.06079","n_code_links":0,"syntology":null},{"paper":null,"slug":"establishing-performance-baselines-in-fine","title":"Establishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users","date":"2023-11-10","arxiv_id":"2311.05903","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-fine-tuning-chatgpt-for-news","title":"Exploring Fine-tuning ChatGPT for News Recommendation","date":"2023-11-10","arxiv_id":"2311.05850","n_code_links":0,"syntology":null},{"paper":null,"slug":"greedy-pig-adaptive-integrated-gradients","title":"Greedy PIG: Adaptive Integrated Gradients","date":"2023-11-10","arxiv_id":"2311.06192","n_code_links":0,"syntology":null},{"paper":null,"slug":"hiformer-heterogeneous-feature-interactions","title":"Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems","date":"2023-11-10","arxiv_id":"2311.05884","n_code_links":0,"syntology":null},{"paper":null,"slug":"how-to-bridge-the-gap-between-modalities-a","title":"How to Bridge the Gap between Modalities: Survey on Multimodal Large Language Model","date":"2023-11-10","arxiv_id":"2311.07594","n_code_links":0,"syntology":null},{"paper":null,"slug":"language-models-can-be-logical-solvers","title":"Language Models can be Logical Solvers","date":"2023-11-10","arxiv_id":"2311.06158","n_code_links":0,"syntology":null},{"paper":null,"slug":"making-llms-worth-every-penny-resource","title":"Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking","date":"2023-11-10","arxiv_id":"2311.06102","n_code_links":0,"syntology":null},{"paper":"/paper/smart-agent-based-modeling-on-the-use-of","slug":"smart-agent-based-modeling-on-the-use-of","title":"Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations","date":"2023-11-10","arxiv_id":"2311.06330","n_code_links":4,"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":["roihn/sabm"],"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/transformcode-a-contrastive-learning","slug":"transformcode-a-contrastive-learning","title":"TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation","date":"2023-11-10","arxiv_id":"2311.08157","n_code_links":1,"syntology":null},{"paper":null,"slug":"yolov5s-bc-an-improved-yolov5s-based-method","title":"YOLOv5s-BC: An improved YOLOv5s-based method for real-time apple detection","date":"2023-11-10","arxiv_id":"2311.05811","n_code_links":0,"syntology":null},{"paper":"/paper/accuracy-of-a-vision-language-model-on","slug":"accuracy-of-a-vision-language-model-on","title":"Multimodal Foundation Models Exploit Text to Make Medical Image Predictions","date":"2023-11-09","arxiv_id":"2311.05591","n_code_links":2,"syntology":null},{"paper":null,"slug":"brainnetdiff-generative-ai-empowers-brain","title":"BrainNetDiff: Generative AI Empowers Brain Network Generation via Multimodal Diffusion Model","date":"2023-11-09","arxiv_id":"2311.05199","n_code_links":0,"syntology":null},{"paper":"/paper/conic10k-a-challenging-math-problem","slug":"conic10k-a-challenging-math-problem","title":"Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset","date":"2023-11-09","arxiv_id":"2311.05113","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-learning-in-computed-tomography","title":"Deep learning in computed tomography pulmonary angiography imaging: a dual-pronged approach for pulmonary embolism detection","date":"2023-11-09","arxiv_id":"2311.05197","n_code_links":0,"syntology":null},{"paper":"/paper/deep-natural-language-feature-learning-for","slug":"deep-natural-language-feature-learning-for","title":"Deep Natural Language Feature Learning for Interpretable Prediction","date":"2023-11-09","arxiv_id":"2311.05754","n_code_links":1,"syntology":null},{"paper":null,"slug":"do-personality-tests-generalize-to-large","title":"Challenging the Validity of Personality Tests for Large Language Models","date":"2023-11-09","arxiv_id":"2311.05297","n_code_links":0,"syntology":null},{"paper":null,"slug":"dynamic-association-learning-of-self","title":"Dynamic Association Learning of Self-Attention and Convolution in Image Restoration","date":"2023-11-09","arxiv_id":"2311.05147","n_code_links":0,"syntology":null},{"paper":null,"slug":"geoformer-predicting-human-mobility-using","title":"GeoFormer: Predicting Human Mobility using Generative Pre-trained Transformer (GPT)","date":"2023-11-09","arxiv_id":"2311.05092","n_code_links":0,"syntology":null}],"record_sha256":"6e61106ebf787589a12e351ae2f27750ddee96b980647194881ac214b75b68f8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}