{"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/large-language-model/papers/41","list_of":"/task/large-language-model","task":"Large Language Model","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":41,"pages_in_order":61,"rows_per_page":100,"rows":[4001,4100],"of":6097,"counts":{"archive_papers_tagged":6097,"with_a_code_link":2250,"where_syntology_ran_a_sample":801,"not_listed_spam_title":0,"listed":6097,"listed_where_code_ran":801,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":683,"every_run_a_failure_of_syntologys_instrument":118,"listed_with_a_run_with_no_instrument_failure":683,"listed_every_run_a_failure_of_syntologys_instrument":118,"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/large-language-model","prev":"/task/large-language-model/papers/40","next":"/task/large-language-model/papers/42","papers":[{"url":null,"slug":"learning-to-rank-for-multiple-retrieval","title":"Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization","date":"2024-10-13","arxiv_id":"2410.09942","repositories_listed":0,"syntology":null},{"url":null,"slug":"lore-logit-ranked-retriever-ensemble-for","title":"LoRE: Logit-Ranked Retriever Ensemble for Enhancing Open-Domain Question Answering","date":"2024-10-13","arxiv_id":"2410.10042","repositories_listed":0,"syntology":null},{"url":null,"slug":"misinfoeval-generative-ai-in-the-era-of","title":"MisinfoEval: Generative AI in the Era of \"Alternative Facts\"","date":"2024-10-13","arxiv_id":"2410.09949","repositories_listed":0,"syntology":null},{"url":null,"slug":"moin-mixture-of-introvert-experts-to-upcycle","title":"MoIN: Mixture of Introvert Experts to Upcycle an LLM","date":"2024-10-13","arxiv_id":"2410.09687","repositories_listed":0,"syntology":null},{"url":null,"slug":"debiasing-vison-language-models-with-text","title":"Debiasing Vison-Language Models with Text-Only Training","date":"2024-10-12","arxiv_id":"2410.09365","repositories_listed":0,"syntology":null},{"url":null,"slug":"extended-japanese-commonsense-morality","title":"Extended Japanese Commonsense Morality Dataset with Masked Token and Label Enhancement","date":"2024-10-12","arxiv_id":"2410.09564","repositories_listed":0,"syntology":null},{"url":null,"slug":"impeding-llm-assisted-cheating-in","title":"Impeding LLM-assisted Cheating in Introductory Programming Assignments via Adversarial Perturbation","date":"2024-10-12","arxiv_id":"2410.09318","repositories_listed":0,"syntology":null},{"url":null,"slug":"aerial-vision-and-language-navigation-via","title":"Aerial Vision-and-Language Navigation via Semantic-Topo-Metric Representation Guided LLM Reasoning","date":"2024-10-11","arxiv_id":"2410.08500","repositories_listed":0,"syntology":null},{"url":null,"slug":"forall-uto-exists-lor-land-l-autonomous","title":"$\\forall$uto$\\exists$$\\lor\\!\\land$L: Autonomous Evaluation of LLMs for Truth Maintenance and Reasoning Tasks","date":"2024-10-11","arxiv_id":"2410.08437","repositories_listed":0,"syntology":null},{"url":null,"slug":"hypothesis-only-biases-in-large-language","title":"Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference","date":"2024-10-11","arxiv_id":"2410.08996","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-model-assisted-bi-level-programming","title":"Language-Model-Assisted Bi-Level Programming for Reward Learning from Internet Videos","date":"2024-10-11","arxiv_id":"2410.09286","repositories_listed":0,"syntology":null},{"url":null,"slug":"llmd-a-large-language-model-for-interpreting","title":"LLMD: A Large Language Model for Interpreting Longitudinal Medical Records","date":"2024-10-11","arxiv_id":"2410.12860","repositories_listed":0,"syntology":null},{"url":null,"slug":"p-folio-evaluating-and-improving-logical","title":"P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains","date":"2024-10-11","arxiv_id":"2410.09207","repositories_listed":0,"syntology":null},{"url":null,"slug":"preferential-normalizing-flows","title":"Preferential Normalizing Flows","date":"2024-10-11","arxiv_id":"2410.08710","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-dynamics-of-social-conventions-in-llm","title":"Emergent social conventions and collective bias in LLM populations","date":"2024-10-11","arxiv_id":"2410.08948","repositories_listed":0,"syntology":null},{"url":null,"slug":"vit3d-alignment-of-llama3-3d-medical-image","title":"ViT3D Alignment of LLaMA3: 3D Medical Image Report Generation","date":"2024-10-11","arxiv_id":"2410.08588","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-framework-for-collaborating-a-large","title":"A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts","date":"2024-10-10","arxiv_id":"2410.11877","repositories_listed":0,"syntology":null},{"url":null,"slug":"animating-the-past-reconstruct-trilobite-via","title":"Animating the Past: Reconstruct Trilobite via Video Generation","date":"2024-10-10","arxiv_id":"2410.14715","repositories_listed":0,"syntology":null},{"url":null,"slug":"crossquant-a-post-training-quantization","title":"CrossQuant: A Post-Training Quantization Method with Smaller Quantization Kernel for Precise Large Language Model Compression","date":"2024-10-10","arxiv_id":"2410.07505","repositories_listed":0,"syntology":null},{"url":null,"slug":"disease-entity-recognition-and-normalization","title":"Disease Entity Recognition and Normalization is Improved with Large Language Model Derived Synthetic Normalized Mentions","date":"2024-10-10","arxiv_id":"2410.07951","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-reinforcement-learning-with-large","title":"Efficient Reinforcement Learning with Large Language Model Priors","date":"2024-10-10","arxiv_id":"2410.07927","repositories_listed":0,"syntology":null},{"url":null,"slug":"lecprompt-a-prompt-based-approach-for-logical","title":"LecPrompt: A Prompt-based Approach for Logical Error Correction with CodeBERT","date":"2024-10-10","arxiv_id":"2410.08241","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-gender-bias-in-code-large-language","title":"Mitigating Gender Bias in Code Large Language Models via Model Editing","date":"2024-10-10","arxiv_id":"2410.07820","repositories_listed":0,"syntology":null},{"url":null,"slug":"optima-optimizing-effectiveness-and","title":"Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System","date":"2024-10-10","arxiv_id":"2410.08115","repositories_listed":0,"syntology":null},{"url":null,"slug":"promptly-yours-a-human-subject-study-on","title":"Promptly Yours? A Human Subject Study on Prompt Inference in AI-Generated Art","date":"2024-10-10","arxiv_id":"2410.08406","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-large-language-model-greeklegalroberta","title":"The Large Language Model GreekLegalRoBERTa","date":"2024-10-10","arxiv_id":"2410.12852","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncovering-overfitting-in-large-language","title":"Uncovering Overfitting in Large Language Model Editing","date":"2024-10-10","arxiv_id":"2410.07819","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-few-shot-detection-with-large","title":"Boosting Few-Shot Detection with Large Language Models and Layout-to-Image Synthesis","date":"2024-10-09","arxiv_id":"2410.06841","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-multimodal-llm-for-detailed-and","title":"Enhancing Multimodal LLM for Detailed and Accurate Video Captioning using Multi-Round Preference Optimization","date":"2024-10-09","arxiv_id":"2410.06682","repositories_listed":0,"syntology":null},{"url":null,"slug":"fltlm-an-intergrated-long-context-large","title":"FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding","date":"2024-10-09","arxiv_id":"2410.06886","repositories_listed":0,"syntology":null},{"url":null,"slug":"lamp-language-motion-pretraining-for-motion","title":"LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning","date":"2024-10-09","arxiv_id":"2410.07093","repositories_listed":0,"syntology":null},{"url":null,"slug":"let-s-ask-gnn-empowering-large-language-model","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","date":"2024-10-09","arxiv_id":"2410.07074","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-compression-with-neural-architecture","title":"Large Language Model Compression with Neural Architecture Search","date":"2024-10-09","arxiv_id":"2410.06479","repositories_listed":0,"syntology":null},{"url":null,"slug":"personal-intelligence-system-unilm-hybrid-on","title":"Personal Intelligence System UniLM: Hybrid On-Device Small Language Model and Server-Based Large Language Model for Malay Nusantara","date":"2024-10-09","arxiv_id":"2410.06973","repositories_listed":0,"syntology":null},{"url":null,"slug":"quailora-quantization-aware-initialization","title":"QuAILoRA: Quantization-Aware Initialization for LoRA","date":"2024-10-09","arxiv_id":"2410.14713","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-advancements-in-llm-red-teaming","title":"Recent advancements in LLM Red-Teaming: Techniques, Defenses, and Ethical Considerations","date":"2024-10-09","arxiv_id":"2410.09097","repositories_listed":0,"syntology":null},{"url":null,"slug":"reproducing-and-extending-experiments-in","title":"Reproducing and Extending Experiments in Behavioral Strategy with Large Language Models","date":"2024-10-09","arxiv_id":"2410.06932","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncovering-factor-level-preferences-to","title":"Uncovering Factor Level Preferences to Improve Human-Model Alignment","date":"2024-10-09","arxiv_id":"2410.06965","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerated-preference-optimization-for-large","title":"Accelerated Preference Optimization for Large Language Model Alignment","date":"2024-10-08","arxiv_id":"2410.06293","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-notebooklm-a-large-language","title":"Application of NotebookLM, a Large Language Model with Retrieval-Augmented Generation, for Lung Cancer Staging","date":"2024-10-08","arxiv_id":"2410.10869","repositories_listed":0,"syntology":null},{"url":null,"slug":"claimbrush-a-novel-framework-for-automated","title":"ClaimBrush: A Novel Framework for Automated Patent Claim Refinement Based on Large Language Models","date":"2024-10-08","arxiv_id":"2410.05575","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoratelm-data-engineering-through-corpus","title":"DecorateLM: Data Engineering through Corpus Rating, Tagging, and Editing with Language Models","date":"2024-10-08","arxiv_id":"2410.05639","repositories_listed":0,"syntology":null},{"url":null,"slug":"jet-expansions-of-residual-computation","title":"Jet Expansions of Residual Computation","date":"2024-10-08","arxiv_id":"2410.06024","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-session-client-centered-treatment","title":"Multi-Session Client-Centered Treatment Outcome Evaluation in Psychotherapy","date":"2024-10-08","arxiv_id":"2410.05824","repositories_listed":0,"syntology":null},{"url":null,"slug":"parallelspec-parallel-drafter-for-efficient","title":"ParallelSpec: Parallel Drafter for Efficient Speculative Decoding","date":"2024-10-08","arxiv_id":"2410.05589","repositories_listed":0,"syntology":null},{"url":null,"slug":"teasergen-generating-teasers-for-long","title":"TeaserGen: Generating Teasers for Long Documentaries","date":"2024-10-08","arxiv_id":"2410.05586","repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-and-masking-preference-profile","title":"Filtering Discomforting Recommendations with Large Language Models","date":"2024-10-07","arxiv_id":"2410.05411","repositories_listed":0,"syntology":null},{"url":null,"slug":"driving-with-regulation-interpretable","title":"Driving with Regulation: Interpretable Decision-Making for Autonomous Vehicles with Retrieval-Augmented Reasoning via LLM","date":"2024-10-07","arxiv_id":"2410.04759","repositories_listed":0,"syntology":null},{"url":null,"slug":"falcon-mamba-the-first-competitive-attention","title":"Falcon Mamba: The First Competitive Attention-free 7B Language Model","date":"2024-10-07","arxiv_id":"2410.05355","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-the-loop-hyper-parameter-optimization-for","title":"In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics","date":"2024-10-07","arxiv_id":"2410.16309","repositories_listed":0,"syntology":null},{"url":null,"slug":"intriguing-properties-of-large-language-and","title":"Intriguing Properties of Large Language and Vision Models","date":"2024-10-07","arxiv_id":"2410.04751","repositories_listed":0,"syntology":null},{"url":null,"slug":"leverage-knowledge-graph-and-large-language","title":"Leverage Knowledge Graph and Large Language Model for Law Article Recommendation: A Case Study of Chinese Criminal Law","date":"2024-10-07","arxiv_id":"2410.04949","repositories_listed":0,"syntology":null},{"url":null,"slug":"respllm-unifying-audio-and-text-with","title":"RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health Prediction","date":"2024-10-07","arxiv_id":"2410.05361","repositories_listed":0,"syntology":null},{"url":null,"slug":"wireless-friendly-window-position","title":"Wireless-Friendly Window Position Optimization for RIS-Aided Outdoor-to-Indoor Networks based on Multi-Modal Large Language Model","date":"2024-10-07","arxiv_id":"2410.20691","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-vision-and-language-navigation-with","title":"Zero-Shot Vision-and-Language Navigation with Collision Mitigation in Continuous Environment","date":"2024-10-07","arxiv_id":"2410.17267","repositories_listed":0,"syntology":null},{"url":null,"slug":"damro-dive-into-the-attention-mechanism-of","title":"DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination","date":"2024-10-06","arxiv_id":"2410.04514","repositories_listed":0,"syntology":null},{"url":null,"slug":"od-stega-llm-based-near-imperceptible","title":"OD-Stega: LLM-Based Near-Imperceptible Steganography via Optimized Distributions","date":"2024-10-06","arxiv_id":"2410.04328","repositories_listed":0,"syntology":null},{"url":null,"slug":"retok-replacing-tokenizer-to-enhance","title":"ReTok: Replacing Tokenizer to Enhance Representation Efficiency in Large Language Model","date":"2024-10-06","arxiv_id":"2410.04335","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-performance-of-human-capable","title":"Assessing the Performance of Human-Capable LLMs -- Are LLMs Coming for Your Job?","date":"2024-10-05","arxiv_id":"2410.16285","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-forecasting-compositional-time-series","title":"Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution","date":"2024-10-05","arxiv_id":"2410.04047","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-large-language-model-based-framework-for","title":"A Large Language Model-based Framework for Semi-Structured Tender Document Retrieval-Augmented Generation","date":"2024-10-04","arxiv_id":"2410.09077","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-agent-leveraging-llms-for-audio","title":"Audio-Agent: Leveraging LLMs For Audio Generation, Editing and Composition","date":"2024-10-04","arxiv_id":"2410.03335","repositories_listed":0,"syntology":null},{"url":null,"slug":"auto-gda-automatic-domain-adaptation-for","title":"Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation","date":"2024-10-04","arxiv_id":"2410.03461","repositories_listed":0,"syntology":null},{"url":null,"slug":"autoregressive-large-language-models-are","title":"Autoregressive Large Language Models are Computationally Universal","date":"2024-10-04","arxiv_id":"2410.03170","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-first-or-text-first-optimising-the","title":"Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks","date":"2024-10-04","arxiv_id":"2410.03062","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-performance-benchmarking","title":"Understanding Large Language Models in Your Pockets: Performance Study on COTS Mobile Devices","date":"2024-10-04","arxiv_id":"2410.03613","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncomp-uncertainty-aware-long-context","title":"UNComp: Uncertainty-Aware Long-Context Compressor for Efficient Large Language Model Inference","date":"2024-10-04","arxiv_id":"2410.03090","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-prompts-to-guide-large-language-models","title":"Using Prompts to Guide Large Language Models in Imitating a Real Person's Language Style","date":"2024-10-04","arxiv_id":"2410.03848","repositories_listed":0,"syntology":null},{"url":null,"slug":"braintransformers-snn-llm","title":"BrainTransformers: SNN-LLM","date":"2024-10-03","arxiv_id":"2410.14687","repositories_listed":0,"syntology":null},{"url":null,"slug":"codepmp-scalable-preference-model-pretraining","title":"CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning","date":"2024-10-03","arxiv_id":"2410.02229","repositories_listed":0,"syntology":null},{"url":null,"slug":"cut-the-crap-an-economical-communication","title":"Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems","date":"2024-10-03","arxiv_id":"2410.02506","repositories_listed":0,"syntology":null},{"url":null,"slug":"determine-then-ensemble-necessity-of-top-k","title":"Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling","date":"2024-10-03","arxiv_id":"2410.03777","repositories_listed":0,"syntology":null},{"url":null,"slug":"grounding-large-language-models-in-embodied","title":"Grounding Large Language Models In Embodied Environment With Imperfect World Models","date":"2024-10-03","arxiv_id":"2410.02742","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-aided-multi-objective","title":"Large Language Model Aided Multi-objective Evolutionary Algorithm: a Low-cost Adaptive Approach","date":"2024-10-03","arxiv_id":"2410.02301","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-for-multi-domain","title":"Large Language Model for Multi-Domain Translation: Benchmarking and Domain CoT Fine-tuning","date":"2024-10-03","arxiv_id":"2410.02631","repositories_listed":0,"syntology":null},{"url":null,"slug":"llmco2-advancing-accurate-carbon-footprint","title":"LLMCO2: Advancing Accurate Carbon Footprint Prediction for LLM Inferences","date":"2024-10-03","arxiv_id":"2410.02950","repositories_listed":0,"syntology":null},{"url":null,"slug":"medvisionllama-leveraging-pre-trained-large","title":"MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation","date":"2024-10-03","arxiv_id":"2410.02458","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-clothing-recommendation-model","title":"Multi-modal clothing recommendation model based on large model and VAE enhancement","date":"2024-10-03","arxiv_id":"2410.02219","repositories_listed":0,"syntology":null},{"url":null,"slug":"neutral-residues-revisiting-adapters-for","title":"Neutral residues: revisiting adapters for model extension","date":"2024-10-03","arxiv_id":"2410.02744","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-world-cooking-robot-system-from-recipes","title":"Real-World Cooking Robot System from Recipes Based on Food State Recognition Using Foundation Models and PDDL","date":"2024-10-03","arxiv_id":"2410.02874","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertaintyrag-span-level-uncertainty","title":"UncertaintyRAG: Span-Level Uncertainty Enhanced Long-Context Modeling for Retrieval-Augmented Generation","date":"2024-10-03","arxiv_id":"2410.02719","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-stage-proactive-dialogue-generator-for","title":"A Two-Stage Proactive Dialogue Generator for Efficient Clinical Information Collection Using Large Language Model","date":"2024-10-02","arxiv_id":"2410.03770","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-weakly-supervised-referring-image","title":"Boosting Weakly-Supervised Referring Image Segmentation via Progressive Comprehension","date":"2024-10-02","arxiv_id":"2410.01544","repositories_listed":0,"syntology":null},{"url":"/paper/chase-sql-multi-path-reasoning-and-preference","slug":"chase-sql-multi-path-reasoning-and-preference","title":"CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL","date":"2024-10-02","arxiv_id":"2410.01943","repositories_listed":0,"syntology":null},{"url":null,"slug":"conserve-harvesting-gpus-for-low-latency-and","title":"ConServe: Harvesting GPUs for Low-Latency and High-Throughput Large Language Model Serving","date":"2024-10-02","arxiv_id":"2410.01228","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-1-bit-tensor-approximations","title":"Efficient $1$-bit tensor approximations","date":"2024-10-02","arxiv_id":"2410.01799","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-reward-shaping-to-q-shaping-achieving","title":"From Reward Shaping to Q-Shaping: Achieving Unbiased Learning with LLM-Guided Knowledge","date":"2024-10-02","arxiv_id":"2410.01458","repositories_listed":0,"syntology":null},{"url":null,"slug":"frozen-large-language-models-can-perceive","title":"Frozen Large Language Models Can Perceive Paralinguistic Aspects of Speech","date":"2024-10-02","arxiv_id":"2410.01162","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-on-rlhf-methodology","title":"Investigating on RLHF methodology","date":"2024-10-02","arxiv_id":"2410.01789","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-large-language-models-to-enhance-1","title":"Leveraging Large Language Models to Enhance Personalized Recommendations in E-commerce","date":"2024-10-02","arxiv_id":"2410.12829","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-augmented-symbolic-reinforcement-learning","title":"LLM-Augmented Symbolic Reinforcement Learning with Landmark-Based Task Decomposition","date":"2024-10-02","arxiv_id":"2410.01929","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-range-gene-expression-prediction-with","title":"Long-range gene expression prediction with token alignment of large language model","date":"2024-10-02","arxiv_id":"2410.01858","repositories_listed":0,"syntology":null},{"url":null,"slug":"occ-mllm-alpha-empowering-multi-modal-large","title":"OCC-MLLM-Alpha:Empowering Multi-modal Large Language Model for the Understanding of Occluded Objects with Self-Supervised Test-Time Learning","date":"2024-10-02","arxiv_id":"2410.01861","repositories_listed":0,"syntology":null},{"url":null,"slug":"occ-mllm-empowering-multimodal-large-language","title":"OCC-MLLM:Empowering Multimodal Large Language Model For the Understanding of Occluded Objects","date":"2024-10-02","arxiv_id":"2410.01261","repositories_listed":0,"syntology":null},{"url":null,"slug":"racing-thoughts-explaining-large-language","title":"Racing Thoughts: Explaining Contextualization Errors in Large Language Models","date":"2024-10-02","arxiv_id":"2410.02102","repositories_listed":0,"syntology":null},{"url":null,"slug":"spoken-grammar-assessment-using-llm","title":"Spoken Grammar Assessment Using LLM","date":"2024-10-02","arxiv_id":"2410.01579","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-the-capabilities-of-compact-models","title":"Boosting the Capabilities of Compact Models in Low-Data Contexts with Large Language Models and Retrieval-Augmented Generation","date":"2024-10-01","arxiv_id":"2410.00387","repositories_listed":0,"syntology":null},{"url":null,"slug":"deteccion-automatica-de-patologias-en-notas","title":"Detección Automática de Patologías en Notas Clínicas en Español Combinando Modelos de Lenguaje y Ontologías Médicos","date":"2024-10-01","arxiv_id":"2410.00616","repositories_listed":0,"syntology":null},{"url":null,"slug":"don-t-stop-me-now-embedding-based-scheduling","title":"Don't Stop Me Now: Embedding Based Scheduling for LLMs","date":"2024-10-01","arxiv_id":"2410.01035","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-text-to-music-models-with","title":"Integrating Text-to-Music Models with Language Models: Composing Long Structured Music Pieces","date":"2024-10-01","arxiv_id":"2410.00344","repositories_listed":0,"syntology":null}],"record_sha256":"fb26827e989477f4dad57cb3a23d39026b7777d4b1e34c031ad96abee40c6917","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}