{"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":"/task/language-modelling/papers/108","list_of":"/task/language-modelling","task":"Language Modelling","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":108,"pages_in_order":177,"rows_per_page":100,"rows":[10701,10800],"of":17610,"counts":{"archive_papers_tagged":17610,"with_a_code_link":7012,"where_syntology_ran_a_sample":2428,"not_listed_spam_title":0,"listed":17610,"listed_where_code_ran":2428,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2027,"every_run_a_failure_of_syntologys_instrument":401,"listed_with_a_run_with_no_instrument_failure":2027,"listed_every_run_a_failure_of_syntologys_instrument":401,"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":"/task/language-modelling","prev":"/task/language-modelling/papers/107","next":"/task/language-modelling/papers/109","papers":[{"url":null,"slug":"wanglab-at-mediqa-corr-2024-optimized-llm","title":"WangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction","date":"2024-04-22","arxiv_id":"2404.14544","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-text-mining-of-experimental","title":"Automated Text Mining of Experimental Methodologies from Biomedical Literature","date":"2024-04-21","arxiv_id":"2404.13779","repositories_listed":0,"syntology":null},{"url":null,"slug":"laser-tuning-free-llm-driven-attention","title":"LASER: Tuning-Free LLM-Driven Attention Control for Efficient Text-conditioned Image-to-Animation","date":"2024-04-21","arxiv_id":"2404.13558","repositories_listed":0,"syntology":null},{"url":null,"slug":"socratic-planner-inquiry-based-zero-shot","title":"Socratic Planner: Self-QA-Based Zero-Shot Planning for Embodied Instruction Following","date":"2024-04-21","arxiv_id":"2404.15190","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-daylight-driven-architectural","title":"Generating Daylight-driven Architectural Design via Diffusion Models","date":"2024-04-20","arxiv_id":"2404.13353","repositories_listed":0,"syntology":null},{"url":null,"slug":"intrusion-detection-at-scale-with-the","title":"Intrusion Detection at Scale with the Assistance of a Command-line Language Model","date":"2024-04-20","arxiv_id":"2404.13402","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-self-consistency-ensemble-reasoning","title":"Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging","date":"2024-04-19","arxiv_id":"2404.13149","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-interactive-semantic-alignment-for","title":"Exploring Interactive Semantic Alignment for Efficient HOI Detection with Vision-language Model","date":"2024-04-19","arxiv_id":"2404.12678","repositories_listed":0,"syntology":null},{"url":null,"slug":"lime-a-latin-corpus-of-late-medieval-criminal","title":"LiMe: a Latin Corpus of Late Medieval Criminal Sentences","date":"2024-04-19","arxiv_id":"2404.12829","repositories_listed":0,"syntology":null},{"url":null,"slug":"accidentblip2-accident-detection-with-multi","title":"AccidentBlip: Agent of Accident Warning based on MA-former","date":"2024-04-18","arxiv_id":"2404.12149","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmenting-emotion-features-in-irony","title":"Augmenting emotion features in irony detection with Large language modeling","date":"2024-04-18","arxiv_id":"2404.12291","repositories_listed":0,"syntology":null},{"url":null,"slug":"concept-induction-using-llms-a-user","title":"Concept Induction using LLMs: a user experiment for assessment","date":"2024-04-18","arxiv_id":"2404.11875","repositories_listed":0,"syntology":null},{"url":null,"slug":"deeplocalization-using-change-point-detection","title":"DeepLocalization: Using change point detection for Temporal Action Localization","date":"2024-04-18","arxiv_id":"2404.12258","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhance-robustness-of-language-models-against","title":"Enhance Robustness of Language Models Against Variation Attack through Graph Integration","date":"2024-04-18","arxiv_id":"2404.12014","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-embedding-performance-through-large","title":"Enhancing Embedding Performance through Large Language Model-based Text Enrichment and Rewriting","date":"2024-04-18","arxiv_id":"2404.12283","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-r-to-q-your-language-model-is-secretly-a","title":"From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function","date":"2024-04-18","arxiv_id":"2404.12358","repositories_listed":0,"syntology":null},{"url":null,"slug":"parallel-decoding-via-hidden-transfer-for","title":"Parallel Decoding via Hidden Transfer for Lossless Large Language Model Acceleration","date":"2024-04-18","arxiv_id":"2404.12022","repositories_listed":0,"syntology":null},{"url":null,"slug":"ragar-your-falsehood-radar-rag-augmented","title":"RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models","date":"2024-04-18","arxiv_id":"2404.12065","repositories_listed":0,"syntology":null},{"url":null,"slug":"skip-skill-localized-prompt-tuning-for","title":"Skeleton: A New Framework for Accelerating Language Models via Task Neuron Localized Prompt Tuning","date":"2024-04-18","arxiv_id":"2404.11916","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-progressive-framework-of-vision-language","title":"A Progressive Framework of Vision-language Knowledge Distillation and Alignment for Multilingual Scene","date":"2024-04-17","arxiv_id":"2404.11249","repositories_listed":0,"syntology":null},{"url":null,"slug":"characterizing-and-modeling-harms-from","title":"Characterizing and modeling harms from interactions with design patterns in AI interfaces","date":"2024-04-17","arxiv_id":"2404.11370","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-models-still-struggle-to-zero-shot","title":"Language Models Still Struggle to Zero-shot Reason about Time Series","date":"2024-04-17","arxiv_id":"2404.11757","repositories_listed":0,"syntology":null},{"url":null,"slug":"lightweight-unsupervised-federated-learning","title":"Lightweight Unsupervised Federated Learning with Pretrained Vision Language Model","date":"2024-04-17","arxiv_id":"2404.11046","repositories_listed":0,"syntology":null},{"url":null,"slug":"longvq-long-sequence-modeling-with-vector","title":"LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory","date":"2024-04-17","arxiv_id":"2404.11163","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-scalability-of-gnns-for-molecular","title":"On the Scalability of GNNs for Molecular Graphs","date":"2024-04-17","arxiv_id":"2404.11568","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-guided-generation-of-structured-chest","title":"Prompt-Guided Generation of Structured Chest X-Ray Report Using a Pre-trained LLM","date":"2024-04-17","arxiv_id":"2404.11209","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-optimizer-of-text-to-image-diffusion","title":"Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding","date":"2024-04-17","arxiv_id":"2404.11589","repositories_listed":0,"syntology":null},{"url":null,"slug":"villm-eval-a-comprehensive-evaluation-suite","title":"ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models","date":"2024-04-17","arxiv_id":"2404.11086","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesjudge-bayesian-kernel-language-modelling","title":"BayesJudge: Bayesian Kernel Language Modelling with Confidence Uncertainty in Legal Judgment Prediction","date":"2024-04-16","arxiv_id":"2404.10481","repositories_listed":0,"syntology":null},{"url":null,"slug":"consistency-and-uncertainty-identifying","title":"Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering","date":"2024-04-16","arxiv_id":"2404.10193","repositories_listed":0,"syntology":null},{"url":null,"slug":"construction-of-domain-specified-japanese","title":"Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training","date":"2024-04-16","arxiv_id":"2404.10555","repositories_listed":0,"syntology":null},{"url":null,"slug":"exact-and-efficient-unlearning-for-large","title":"Exact and Efficient Unlearning for Large Language Model-based Recommendation","date":"2024-04-16","arxiv_id":"2404.10327","repositories_listed":0,"syntology":null},{"url":null,"slug":"fewer-truncations-improve-language-modeling","title":"Fewer Truncations Improve Language Modeling","date":"2024-04-16","arxiv_id":"2404.10830","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-a-lossless-1-5-1-compression-algorithm","title":"From a Lossless (~1.5:1) Compression Algorithm for Llama2 7B Weights to Variable Precision, Variable Range, Compressed Numeric Data Types for CNNs and LLMs","date":"2024-04-16","arxiv_id":"2404.10896","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-text-steganography-with-large","title":"Generative Text Steganography with Large Language Model","date":"2024-04-16","arxiv_id":"2404.10229","repositories_listed":0,"syntology":null},{"url":null,"slug":"reasoning-on-efficient-knowledge-paths","title":"Reasoning on Efficient Knowledge Paths:Knowledge Graph Guides Large Language Model for Domain Question Answering","date":"2024-04-16","arxiv_id":"2404.10384","repositories_listed":0,"syntology":null},{"url":null,"slug":"white-men-lead-black-women-help-uncovering","title":"White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs","date":"2024-04-16","arxiv_id":"2404.10508","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatshop-interactive-information-seeking-with","title":"ChatShop: Interactive Information Seeking with Language Agents","date":"2024-04-15","arxiv_id":"2404.09911","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-llms-understand-visual-anomalies","title":"Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection","date":"2024-04-15","arxiv_id":"2404.09654","repositories_listed":0,"syntology":null},{"url":null,"slug":"evolving-interpretable-visual-classifiers","title":"Evolving Interpretable Visual Classifiers with Large Language Models","date":"2024-04-15","arxiv_id":"2404.09941","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-model-cascades-token-level","title":"Language Model Cascades: Token-level uncertainty and beyond","date":"2024-04-15","arxiv_id":"2404.10136","repositories_listed":0,"syntology":null},{"url":null,"slug":"learn-your-reference-model-for-real-good","title":"Learn Your Reference Model for Real Good Alignment","date":"2024-04-15","arxiv_id":"2404.09656","repositories_listed":0,"syntology":null},{"url":null,"slug":"prodis-a-speech-database-and-a-phoneme-based","title":"PRODIS - a speech database and a phoneme-based language model for the study of predictability effects in Polish","date":"2024-04-15","arxiv_id":"2404.10112","repositories_listed":0,"syntology":null},{"url":null,"slug":"uniaa-a-unified-multi-modal-image-aesthetic","title":"UNIAA: A Unified Multi-modal Image Aesthetic Assessment Baseline and Benchmark","date":"2024-04-15","arxiv_id":"2404.09619","repositories_listed":0,"syntology":null},{"url":null,"slug":"unveiling-imitation-learning-exploring-the","title":"Unveiling Imitation Learning: Exploring the Impact of Data Falsity to Large Language Model","date":"2024-04-15","arxiv_id":"2404.09717","repositories_listed":0,"syntology":null},{"url":null,"slug":"compass-large-multilingual-language-model-for","title":"Compass: Large Multilingual Language Model for South-east Asia","date":"2024-04-14","arxiv_id":"2404.09220","repositories_listed":0,"syntology":null},{"url":"/paper/detclipv3-towards-versatile-generative-open","slug":"detclipv3-towards-versatile-generative-open","title":"DetCLIPv3: Towards Versatile Generative Open-vocabulary Object Detection","date":"2024-04-14","arxiv_id":"2404.09216","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-generative-ai-agents-for","title":"Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission","date":"2024-04-14","arxiv_id":"2404.09134","repositories_listed":0,"syntology":null},{"url":null,"slug":"jafin-japanese-financial-instruction-dataset","title":"JaFIn: Japanese Financial Instruction Dataset","date":"2024-04-14","arxiv_id":"2404.09260","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledgeable-agents-by-offline-reinforcement","title":"Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts","date":"2024-04-14","arxiv_id":"2404.09248","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-selected-attention-span-for-accelerating","title":"Self-Selected Attention Span for Accelerating Large Language Model Inference","date":"2024-04-14","arxiv_id":"2404.09336","repositories_listed":0,"syntology":null},{"url":null,"slug":"test-code-generation-for-telecom-software","title":"Test Code Generation for Telecom Software Systems using Two-Stage Generative Model","date":"2024-04-14","arxiv_id":"2404.09249","repositories_listed":0,"syntology":null},{"url":null,"slug":"text2taste-a-versatile-egocentric-vision","title":"TEXT2TASTE: A Versatile Egocentric Vision System for Intelligent Reading Assistance Using Large Language Model","date":"2024-04-14","arxiv_id":"2404.09254","repositories_listed":0,"syntology":null},{"url":null,"slug":"adapting-mental-health-prediction-tasks-for","title":"Adapting Mental Health Prediction Tasks for Cross-lingual Learning via Meta-Training and In-context Learning with Large Language Model","date":"2024-04-13","arxiv_id":"2404.09045","repositories_listed":0,"syntology":null},{"url":null,"slug":"chimpvlm-ethogram-enhanced-chimpanzee","title":"ChimpVLM: Ethogram-Enhanced Chimpanzee Behaviour Recognition","date":"2024-04-13","arxiv_id":"2404.08937","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-ai-agent-for-next-generation-mimo","title":"Generative AI Agent for Next-Generation MIMO Design: Fundamentals, Challenges, and Vision","date":"2024-04-13","arxiv_id":"2404.08878","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-large-language-model-as-simulated","title":"Leveraging Large Language Model as Simulated Patients for Clinical Education","date":"2024-04-13","arxiv_id":"2404.13066","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-speculative-decoding-for-multimodal-large","title":"On Speculative Decoding for Multimodal Large Language Models","date":"2024-04-13","arxiv_id":"2404.08856","repositories_listed":0,"syntology":null},{"url":null,"slug":"cuda-accelerated-soft-robot-neural-evolution","title":"CUDA-Accelerated Soft Robot Neural Evolution with Large Language Model Supervision","date":"2024-04-12","arxiv_id":"2405.00698","repositories_listed":0,"syntology":null},{"url":null,"slug":"emerging-property-of-masked-token-for","title":"Emerging Property of Masked Token for Effective Pre-training","date":"2024-04-12","arxiv_id":"2404.08330","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-quality-of-answers-in","title":"Measuring the Quality of Answers in Political Q&As with Large Language Models","date":"2024-04-12","arxiv_id":"2404.08816","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-model-prompt-selection-via","title":"Language Model Prompt Selection via Simulation Optimization","date":"2024-04-12","arxiv_id":"2404.08164","repositories_listed":0,"syntology":null},{"url":null,"slug":"pretraining-and-updating-language-and-domain","title":"Pretraining and Updates of Domain-Specific LLM: A Case Study in the Japanese Business Domain","date":"2024-04-12","arxiv_id":"2404.08262","repositories_listed":0,"syntology":null},{"url":null,"slug":"rlhf-deciphered-a-critical-analysis-of","title":"RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs","date":"2024-04-12","arxiv_id":"2404.08555","repositories_listed":0,"syntology":null},{"url":null,"slug":"thematic-analysis-with-large-language-models","title":"Thematic Analysis with Large Language Models: does it work with languages other than English? A targeted test in Italian","date":"2024-04-12","arxiv_id":"2404.08488","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-a-theory-of-tokenization-in-llms","title":"Toward a Theory of Tokenization in LLMs","date":"2024-04-12","arxiv_id":"2404.08335","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-a-vision-language-model-as","title":"Training a Vision Language Model as Smartphone Assistant","date":"2024-04-12","arxiv_id":"2404.08755","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-expert-large-language-model","title":"A Multi-Expert Large Language Model Architecture for Verilog Code Generation","date":"2024-04-11","arxiv_id":"2404.08029","repositories_listed":0,"syntology":null},{"url":null,"slug":"auctions-with-llm-summaries","title":"Auctions with LLM Summaries","date":"2024-04-11","arxiv_id":"2404.08126","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-dialogues-dialogues-dataset-for-audio","title":"Audio Dialogues: Dialogues dataset for audio and music understanding","date":"2024-04-11","arxiv_id":"2404.07616","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-portfolio-management-for-motion","title":"Data-Driven Portfolio Management for Motion Pictures Industry: A New Data-Driven Optimization Methodology Using a Large Language Model as the Expert","date":"2024-04-11","arxiv_id":"2404.07434","repositories_listed":0,"syntology":null},{"url":null,"slug":"distilling-algorithmic-reasoning-from-llms","title":"Distilling Algorithmic Reasoning from LLMs via Explaining Solution Programs","date":"2024-04-11","arxiv_id":"2404.08148","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-latency-conversational-turns-for-spoken","title":"Human Latency Conversational Turns for Spoken Avatar Systems","date":"2024-04-11","arxiv_id":"2404.16053","repositories_listed":0,"syntology":null},{"url":null,"slug":"introducing-l2m3-a-multilingual-medical-large","title":"Introducing L2M3, A Multilingual Medical Large Language Model to Advance Health Equity in Low-Resource Regions","date":"2024-04-11","arxiv_id":"2404.08705","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-can-continue-evolving","title":"CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From Mistakes","date":"2024-04-11","arxiv_id":"2404.08707","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-emotion-recognition-by-fusing","title":"Multimodal Emotion Recognition by Fusing Video Semantic in MOOC Learning Scenarios","date":"2024-04-11","arxiv_id":"2404.07484","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-unified-prompt-tuning-for-request-quality","title":"On Unified Prompt Tuning for Request Quality Assurance in Public Code Review","date":"2024-04-11","arxiv_id":"2404.07942","repositories_listed":0,"syntology":null},{"url":null,"slug":"protein-intrinsic-disorder-prediction-using","title":"DisorderUnetLM: Validating ProteinUnet for efficient protein intrinsic disorder prediction","date":"2024-04-11","arxiv_id":"2404.08108","repositories_listed":0,"syntology":null},{"url":null,"slug":"researchagent-iterative-research-idea","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","date":"2024-04-11","arxiv_id":"2404.07738","repositories_listed":0,"syntology":null},{"url":null,"slug":"risklabs-predicting-financial-risk-using","title":"RiskLabs: Predicting Financial Risk Using Large Language Model based on Multimodal and Multi-Sources Data","date":"2024-04-11","arxiv_id":"2404.07452","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-future-of-scientific-publishing-automated","title":"The Future of Scientific Publishing: Automated Article Generation","date":"2024-04-11","arxiv_id":"2404.17586","repositories_listed":0,"syntology":null},{"url":null,"slug":"why-do-small-language-models-underperform","title":"Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck","date":"2024-04-11","arxiv_id":"2404.07647","repositories_listed":0,"syntology":null},{"url":null,"slug":"accuracy-of-a-large-language-model-in","title":"Accuracy of a Large Language Model in Distinguishing Anti- And Pro-vaccination Messages on Social Media: The Case of Human Papillomavirus Vaccination","date":"2024-04-10","arxiv_id":"2404.06731","repositories_listed":0,"syntology":null},{"url":null,"slug":"brave-broadening-the-visual-encoding-of","title":"BRAVE: Broadening the visual encoding of vision-language models","date":"2024-04-10","arxiv_id":"2404.07204","repositories_listed":0,"syntology":null},{"url":null,"slug":"frontier-ai-ethics-anticipating-and","title":"Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agents","date":"2024-04-10","arxiv_id":"2404.06750","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-language-model-reasoning-with-self","title":"Improving Language Model Reasoning with Self-motivated Learning","date":"2024-04-10","arxiv_id":"2404.07017","repositories_listed":0,"syntology":null},{"url":null,"slug":"medrg-medical-report-grounding-with-multi","title":"MedRG: Medical Report Grounding with Multi-modal Large Language Model","date":"2024-04-10","arxiv_id":"2404.06798","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-cross-layer-energy-optimizations-in","title":"Toward Cross-Layer Energy Optimizations in AI Systems","date":"2024-04-10","arxiv_id":"2404.06675","repositories_listed":0,"syntology":null},{"url":null,"slug":"agentscodriver-large-language-model-empowered","title":"AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning","date":"2024-04-09","arxiv_id":"2404.06345","repositories_listed":0,"syntology":null},{"url":null,"slug":"anchor-based-robust-finetuning-of-vision","title":"Anchor-based Robust Finetuning of Vision-Language Models","date":"2024-04-09","arxiv_id":"2404.06244","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-extraction-in-basque-typologically","title":"Event Extraction in Basque: Typologically motivated Cross-Lingual Transfer-Learning Analysis","date":"2024-04-09","arxiv_id":"2404.06392","repositories_listed":0,"syntology":null},{"url":null,"slug":"guide-graphical-user-interface-data-for","title":"GUIDE: Graphical User Interface Data for Execution","date":"2024-04-09","arxiv_id":"2404.16048","repositories_listed":0,"syntology":null},{"url":null,"slug":"less-is-more-for-improving-automatic","title":"Less is More for Improving Automatic Evaluation of Factual Consistency","date":"2024-04-09","arxiv_id":"2404.06579","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-driven-universal-model-for-view","title":"Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis","date":"2024-04-09","arxiv_id":"2404.05916","repositories_listed":0,"syntology":null},{"url":null,"slug":"automating-research-synthesis-with-domain","title":"Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning","date":"2024-04-08","arxiv_id":"2404.08680","repositories_listed":0,"syntology":null},{"url":null,"slug":"constraining-large-language-model-for","title":"Guiding Large Language Models to Generate Computer-Parsable Content","date":"2024-04-08","arxiv_id":"2404.05499","repositories_listed":0,"syntology":null},{"url":null,"slug":"dlora-distributed-parameter-efficient-fine","title":"DLoRA: Distributed Parameter-Efficient Fine-Tuning Solution for Large Language Model","date":"2024-04-08","arxiv_id":"2404.05182","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-clinical-efficiency-through-llm","title":"Enhancing Clinical Efficiency through LLM: Discharge Note Generation for Cardiac Patients","date":"2024-04-08","arxiv_id":"2404.05144","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-english-the-new-programming-language-how","title":"Is English the New Programming Language? How About Pseudo-code Engineering?","date":"2024-04-08","arxiv_id":"2404.08684","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-augmented-retrieval-enhancing-retrieval","title":"LLM-Augmented Retrieval: Enhancing Retrieval Models Through Language Models and Doc-Level Embedding","date":"2024-04-08","arxiv_id":"2404.05825","repositories_listed":0,"syntology":null}],"record_sha256":"757d541bf03a4fdd3cf7e3d464e56b3abe4507c643f1faf43114ee27545a05dc","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}