{"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/48","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":48,"pages_in_order":61,"rows_per_page":100,"rows":[4701,4800],"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/47","next":"/task/large-language-model/papers/49","papers":[{"url":null,"slug":"large-language-model-enabled-multi-agent","title":"Large Language Model-Enabled Multi-Agent Manufacturing Systems","date":"2024-06-04","arxiv_id":"2406.01893","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-network-enhanced-retrieval-for","title":"Graph Neural Network Enhanced Retrieval for Question Answering of LLMs","date":"2024-06-03","arxiv_id":"2406.06572","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-understand-whole-software-repository","title":"Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Exploration","date":"2024-06-03","arxiv_id":"2406.01422","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-assisted-optimal-bidding","title":"Large Language Model Assisted Optimal Bidding of BESS in FCAS Market: An AI-agent based Approach","date":"2024-06-03","arxiv_id":"2406.00974","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-and-gnn-are-complementary-distilling-llm","title":"LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning","date":"2024-06-03","arxiv_id":"2406.01032","repositories_listed":0,"syntology":null},{"url":null,"slug":"revolutionizing-large-language-model-training","title":"SwitchLoRA: Switched Low-Rank Adaptation Can Learn Full-Rank Information","date":"2024-06-03","arxiv_id":"2406.06564","repositories_listed":0,"syntology":null},{"url":null,"slug":"superhuman-performance-in-urology-board","title":"Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study","date":"2024-06-03","arxiv_id":"2406.01428","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-distractor-generation-via-large","title":"Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding","date":"2024-06-03","arxiv_id":"2406.01306","repositories_listed":0,"syntology":null},{"url":null,"slug":"longskywork-a-training-recipe-for-efficiently","title":"LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models","date":"2024-06-02","arxiv_id":"2406.00605","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-copilot-in-bim-authoring-tool-using","title":"Towards a copilot in BIM authoring tool using a large language model-based agent for intelligent human-machine interaction","date":"2024-06-02","arxiv_id":"2406.16903","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-large-language-model-agents-with","title":"Controlling Large Language Model Agents with Entropic Activation Steering","date":"2024-06-01","arxiv_id":"2406.00244","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-confidence-estimation","title":"Large Language Model Confidence Estimation via Black-Box Access","date":"2024-06-01","arxiv_id":"2406.04370","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-overcoming-miscalibrated-conversational","title":"On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots","date":"2024-06-01","arxiv_id":"2406.01633","repositories_listed":0,"syntology":null},{"url":null,"slug":"wav2prompt-end-to-end-speech-prompt","title":"Wav2Prompt: End-to-End Speech Prompt Generation and Tuning For LLM in Zero and Few-shot Learning","date":"2024-06-01","arxiv_id":"2406.00522","repositories_listed":0,"syntology":null},{"url":null,"slug":"fineradscore-a-radiology-report-line-by-line","title":"FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores","date":"2024-05-31","arxiv_id":"2405.20613","repositories_listed":0,"syntology":null},{"url":null,"slug":"rag-does-not-work-for-enterprises","title":"RAG Does Not Work for Enterprises","date":"2024-05-31","arxiv_id":"2406.04369","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-llm-jailbreaking-by-introducing","title":"Efficient Indirect LLM Jailbreak via Multimodal-LLM Jailbreak","date":"2024-05-30","arxiv_id":"2405.20015","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-words-to-actions-unveiling-the","title":"From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems","date":"2024-05-30","arxiv_id":"2405.19883","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graph-tuning-real-time-large","title":"Knowledge Graph Tuning: Real-time Large Language Model Personalization based on Human Feedback","date":"2024-05-30","arxiv_id":"2405.19686","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-watermark-stealing-with","title":"Large Language Model Watermark Stealing With Mixed Integer Programming","date":"2024-05-30","arxiv_id":"2405.19677","repositories_listed":0,"syntology":null},{"url":null,"slug":"specdec-boosting-speculative-decoding-via","title":"SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths","date":"2024-05-30","arxiv_id":"2405.19715","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-full-duplex-speech-dialogue-scheme-based-on","title":"A Full-duplex Speech Dialogue Scheme Based On Large Language Models","date":"2024-05-29","arxiv_id":"2405.19487","repositories_listed":0,"syntology":null},{"url":null,"slug":"gemini-physical-world-large-language-models","title":"Gemini & Physical World: Large Language Models Can Estimate the Intensity of Earthquake Shaking from Multi-Modal Social Media Posts","date":"2024-05-29","arxiv_id":"2405.18732","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-litigation-graphs-and-llms-for","title":"Learning from Litigation: Graphs and LLMs for Retrieval and Reasoning in eDiscovery","date":"2024-05-29","arxiv_id":"2405.19164","repositories_listed":0,"syntology":null},{"url":null,"slug":"llama-reg-using-llama-2-for-unsupervised","title":"LLaMA-Reg: Using LLaMA 2 for Unsupervised Medical Image Registration","date":"2024-05-29","arxiv_id":"2405.18774","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-modal-generative-embedding-model","title":"Multi-Modal Generative Embedding Model","date":"2024-05-29","arxiv_id":"2405.19333","repositories_listed":0,"syntology":null},{"url":null,"slug":"to-fp8-and-back-again-quantifying-the-effects","title":"To FP8 and Back Again: Quantifying Reduced Precision Effects on LLM Training Stability","date":"2024-05-29","arxiv_id":"2405.18710","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-layer-retrieval-augmented-generation","title":"Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study","date":"2024-05-29","arxiv_id":"2405.19519","repositories_listed":0,"syntology":null},{"url":null,"slug":"x-vila-cross-modality-alignment-for-large","title":"X-VILA: Cross-Modality Alignment for Large Language Model","date":"2024-05-29","arxiv_id":"2405.19335","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-real-world-sustainability-data","title":"Automated Real-World Sustainability Data Generation from Images of Buildings","date":"2024-05-28","arxiv_id":"2405.18064","repositories_listed":0,"syntology":null},{"url":null,"slug":"don-t-forget-to-connect-improving-rag-with","title":"Don't Forget to Connect! Improving RAG with Graph-based Reranking","date":"2024-05-28","arxiv_id":"2405.18414","repositories_listed":0,"syntology":null},{"url":null,"slug":"facilitating-holistic-evaluations-with-llms","title":"Facilitating Holistic Evaluations with LLMs: Insights from Scenario-Based Experiments","date":"2024-05-28","arxiv_id":"2405.17728","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-a-3d-tokenized-llm-the-key-to-reliable","title":"Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?","date":"2024-05-28","arxiv_id":"2405.18361","repositories_listed":0,"syntology":null},{"url":null,"slug":"mindformer-a-transformer-architecture-for","title":"MindFormer: Semantic Alignment of Multi-Subject fMRI for Brain Decoding","date":"2024-05-28","arxiv_id":"2405.17720","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-are-beacons-a-semantic-perspective","title":"Semantic are Beacons: A Semantic Perspective for Unveiling Parameter-Efficient Fine-Tuning in Knowledge Learning","date":"2024-05-28","arxiv_id":"2405.18292","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-only-synthesis-for-image-captioning","title":"Text-only Synthesis for Image Captioning","date":"2024-05-28","arxiv_id":"2405.18258","repositories_listed":0,"syntology":null},{"url":null,"slug":"xl3m-a-training-free-framework-for-llm-length","title":"XL3M: A Training-free Framework for LLM Length Extension Based on Segment-wise Inference","date":"2024-05-28","arxiv_id":"2405.17755","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-large-language-model-based-multi-agent","title":"A Large Language Model-based multi-agent manufacturing system for intelligent shopfloor","date":"2024-05-27","arxiv_id":"2405.16887","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-backdoor-attacks-against-large","title":"Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-based Decision-Making Systems","date":"2024-05-27","arxiv_id":"2405.20774","repositories_listed":0,"syntology":null},{"url":null,"slug":"larm-large-auto-regressive-model-for-long","title":"LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence","date":"2024-05-27","arxiv_id":"2405.17424","repositories_listed":0,"syntology":null},{"url":null,"slug":"matryoshka-multimodal-models","title":"Matryoshka Multimodal Models","date":"2024-05-27","arxiv_id":"2405.17430","repositories_listed":0,"syntology":null},{"url":null,"slug":"nv-embed-improved-techniques-for-training","title":"NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models","date":"2024-05-27","arxiv_id":"2405.17428","repositories_listed":0,"syntology":null},{"url":null,"slug":"salutary-labeling-with-zero-human-annotation","title":"Salutary Labeling with Zero Human Annotation","date":"2024-05-27","arxiv_id":"2405.17627","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-corrected-multimodal-large-language","title":"Self-Corrected Multimodal Large Language Model for End-to-End Robot Manipulation","date":"2024-05-27","arxiv_id":"2405.17418","repositories_listed":0,"syntology":null},{"url":null,"slug":"selfcp-compressing-long-prompt-to-1-12-using","title":"SelfCP: Compressing Over-Limit Prompt via the Frozen Large Language Model Itself","date":"2024-05-27","arxiv_id":"2405.17052","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-economic-implications-of-large-language","title":"The Economic Implications of Large Language Model Selection on Earnings and Return on Investment: A Decision Theoretic Model","date":"2024-05-27","arxiv_id":"2405.17637","repositories_listed":0,"syntology":null},{"url":null,"slug":"chain-of-tools-large-language-model-is-an","title":"Chain of Tools: Large Language Model is an Automatic Multi-tool Learner","date":"2024-05-26","arxiv_id":"2405.16533","repositories_listed":0,"syntology":null},{"url":null,"slug":"m-rag-reinforcing-large-language-model","title":"M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions","date":"2024-05-26","arxiv_id":"2405.16420","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-rental-price-of-lane-houses-in","title":"Predicting Rental Price of Lane Houses in Shanghai with Machine Learning Methods and Large Language Models","date":"2024-05-26","arxiv_id":"2405.17505","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthesizing-programmatic-reinforcement","title":"Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search","date":"2024-05-26","arxiv_id":"2405.16450","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-statistical-framework-for-weak-to-strong","title":"A transfer learning framework for weak-to-strong generalization","date":"2024-05-25","arxiv_id":"2405.16236","repositories_listed":0,"syntology":null},{"url":null,"slug":"c3llm-conditional-multimodal-content","title":"C3LLM: Conditional Multimodal Content Generation Using Large Language Models","date":"2024-05-25","arxiv_id":"2405.16136","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisit-extend-and-enhance-hessian-free","title":"Revisit, Extend, and Enhance Hessian-Free Influence Functions","date":"2024-05-25","arxiv_id":"2405.17490","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-importance-aware-communications-with","title":"Semantic Importance-Aware Communications with Semantic Correction Using Large Language Models","date":"2024-05-25","arxiv_id":"2405.16011","repositories_listed":0,"syntology":null},{"url":null,"slug":"decoding-at-the-speed-of-thought-harnessing","title":"Decoding at the Speed of Thought: Harnessing Parallel Decoding of Lexical Units for LLMs","date":"2024-05-24","arxiv_id":"2405.15208","repositories_listed":0,"syntology":null},{"url":null,"slug":"decompose-and-aggregate-a-step-by-step","title":"DnA-Eval: Enhancing Large Language Model Evaluation through Decomposition and Aggregation","date":"2024-05-24","arxiv_id":"2405.15329","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-reinforcement-learning-via-large","title":"Extracting Heuristics from Large Language Models for Reward Shaping in Reinforcement Learning","date":"2024-05-24","arxiv_id":"2405.15194","repositories_listed":0,"syntology":null},{"url":null,"slug":"gecko-generative-language-model-for-english","title":"GECKO: Generative Language Model for English, Code and Korean","date":"2024-05-24","arxiv_id":"2405.15640","repositories_listed":0,"syntology":null},{"url":null,"slug":"inverse-rlignment-inverse-reinforcement","title":"Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning","date":"2024-05-24","arxiv_id":"2405.15624","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-llm-for-standard-cell","title":"Large Language Model (LLM) for Standard Cell Layout Design Optimization","date":"2024-05-24","arxiv_id":"2406.06549","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-pruning","title":"Large Language Model Pruning","date":"2024-05-24","arxiv_id":"2406.00030","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-sentinel-advancing","title":"Large Language Model Sentinel: LLM Agent for Adversarial Purification","date":"2024-05-24","arxiv_id":"2405.20770","repositories_listed":0,"syntology":null},{"url":null,"slug":"raee-a-training-free-retrieval-augmented","title":"RAEE: A Robust Retrieval-Augmented Early Exiting Framework for Efficient Inference","date":"2024-05-24","arxiv_id":"2405.15198","repositories_listed":0,"syntology":null},{"url":"/paper/synergizing-in-context-learning-with-hints","slug":"synergizing-in-context-learning-with-hints","title":"Synergizing In-context Learning with Hints for End-to-end Task-oriented Dialog Systems","date":"2024-05-24","arxiv_id":"2405.15585","repositories_listed":0,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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) · 1 unverified","sample_list":"/paper/synergizing-in-context-learning-with-hints#ran","syntology_url":"https://syntology.ai/paper/2405.15585","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.15585"}},"official":null}},{"url":"/paper/aligngpt-multi-modal-large-language-models","slug":"aligngpt-multi-modal-large-language-models","title":"AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability","date":"2024-05-23","arxiv_id":"2405.14129","repositories_listed":0,"syntology":null},{"url":null,"slug":"aya-23-open-weight-releases-to-further","title":"Aya 23: Open Weight Releases to Further Multilingual Progress","date":"2024-05-23","arxiv_id":"2405.15032","repositories_listed":0,"syntology":null},{"url":null,"slug":"citygpt-towards-urban-iot-learning-analysis","title":"CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System","date":"2024-05-23","arxiv_id":"2405.14691","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-identification-for-french-in-written","title":"Emotion Identification for French in Written Texts: Considering their Modes of Expression as a Step Towards Text Complexity Analysis","date":"2024-05-23","arxiv_id":"2405.14385","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-use-of-a-large-language-model","title":"Exploring the use of a Large Language Model for data extraction in systematic reviews: a rapid feasibility study","date":"2024-05-23","arxiv_id":"2405.14445","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-echoes-a-simple-unified-transformer","title":"Visual Echoes: A Simple Unified Transformer for Audio-Visual Generation","date":"2024-05-23","arxiv_id":"2405.14598","repositories_listed":0,"syntology":null},{"url":"/paper/adapting-multi-modal-large-language-model-to","slug":"adapting-multi-modal-large-language-model-to","title":"Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards","date":"2024-05-22","arxiv_id":"2405.13459","repositories_listed":0,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":1,"phrase":"7 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/adapting-multi-modal-large-language-model-to#ran","syntology_url":"https://syntology.ai/paper/2405.13459","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.13459"}},"official":null}},{"url":null,"slug":"ai-assisted-assessment-of-coding-practices-in","title":"AI-Assisted Assessment of Coding Practices in Modern Code Review","date":"2024-05-22","arxiv_id":"2405.13565","repositories_listed":0,"syntology":null},{"url":null,"slug":"eclipse-semantic-entropy-lcs-for-cross","title":"ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing","date":"2024-05-22","arxiv_id":"2405.13548","repositories_listed":0,"syntology":null},{"url":null,"slug":"fidelis-faithful-reasoning-in-large-language","title":"FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering","date":"2024-05-22","arxiv_id":"2405.13873","repositories_listed":0,"syntology":null},{"url":null,"slug":"ku-dmis-at-ehrsql-2024-generating-sql-query","title":"KU-DMIS at EHRSQL 2024:Generating SQL query via question templatization in EHR","date":"2024-05-22","arxiv_id":"2406.00014","repositories_listed":0,"syntology":null},{"url":null,"slug":"context-enhanced-video-moment-retrieval-with","title":"Context-Enhanced Video Moment Retrieval with Large Language Models","date":"2024-05-21","arxiv_id":"2405.12540","repositories_listed":0,"syntology":null},{"url":null,"slug":"kg-rag-bridging-the-gap-between-knowledge-and","title":"KG-RAG: Bridging the Gap Between Knowledge and Creativity","date":"2024-05-20","arxiv_id":"2405.12035","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-in-context-reasoning-effects-and","title":"Quantifying In-Context Reasoning Effects and Memorization Effects in LLMs","date":"2024-05-20","arxiv_id":"2405.11880","repositories_listed":0,"syntology":null},{"url":null,"slug":"recommender-algorithm-for-supporting-self","title":"Recommender Algorithm for Supporting Self-Management of CVD Risk Factors in an Adult Population at Home","date":"2024-05-20","arxiv_id":"2405.11967","repositories_listed":0,"syntology":null},{"url":null,"slug":"scientific-hypothesis-generation-by-a-large","title":"Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment","date":"2024-05-20","arxiv_id":"2405.12258","repositories_listed":0,"syntology":null},{"url":null,"slug":"style-improving-domain-transferability-of","title":"STYLE: Improving Domain Transferability of Asking Clarification Questions in Large Language Model Powered Conversational Agents","date":"2024-05-20","arxiv_id":"2405.12059","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-method-on-searching-better-activation","title":"A Method on Searching Better Activation Functions","date":"2024-05-19","arxiv_id":"2405.12954","repositories_listed":0,"syntology":null},{"url":null,"slug":"cps-llm-large-language-model-based-safe-usage","title":"CPS-LLM: Large Language Model based Safe Usage Plan Generator for Human-in-the-Loop Human-in-the-Plant Cyber-Physical System","date":"2024-05-19","arxiv_id":"2405.11458","repositories_listed":0,"syntology":null},{"url":null,"slug":"embsum-leveraging-the-summarization","title":"EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations","date":"2024-05-19","arxiv_id":"2405.11441","repositories_listed":0,"syntology":null},{"url":null,"slug":"automating-ptsd-diagnostics-in-clinical","title":"Automating PTSD Diagnostics in Clinical Interviews: Leveraging Large Language Models for Trauma Assessments","date":"2024-05-18","arxiv_id":"2405.11178","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-cap-principle-for-llm-serving","title":"The CAP Principle for LLM Serving: A Survey of Long-Context Large Language Model Serving","date":"2024-05-18","arxiv_id":"2405.11299","repositories_listed":0,"syntology":null},{"url":null,"slug":"activellm-large-language-model-based-active","title":"ActiveLLM: Large Language Model-based Active Learning for Textual Few-Shot Scenarios","date":"2024-05-17","arxiv_id":"2405.10808","repositories_listed":0,"syntology":null},{"url":null,"slug":"audiosetmix-enhancing-audio-language-datasets","title":"AudioSetMix: Enhancing Audio-Language Datasets with LLM-Assisted Augmentations","date":"2024-05-17","arxiv_id":"2405.11093","repositories_listed":0,"syntology":null},{"url":null,"slug":"cognet-md-an-evaluation-framework-and-dataset","title":"COGNET-MD, an evaluation framework and dataset for Large Language Model benchmarks in the medical domain","date":"2024-05-17","arxiv_id":"2405.10893","repositories_listed":0,"syntology":null},{"url":null,"slug":"enova-autoscaling-towards-cost-effective-and","title":"ENOVA: Autoscaling towards Cost-effective and Stable Serverless LLM Serving","date":"2024-05-17","arxiv_id":"2407.09486","repositories_listed":0,"syntology":null},{"url":"/paper/evaluation-of-large-language-model","slug":"evaluation-of-large-language-model","title":"Evaluation of large language model performance on the Biomedical Language Understanding and Reasoning Benchmark","date":"2024-05-17","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-llm-for","title":"Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities","date":"2024-05-17","arxiv_id":"2405.10825","repositories_listed":0,"syntology":null},{"url":null,"slug":"signllm-sign-languages-production-large","title":"SignLLM: Sign Language Production Large Language Models","date":"2024-05-17","arxiv_id":"2405.10718","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-future-of-large-language-model-pre","title":"The Future of Large Language Model Pre-training is Federated","date":"2024-05-17","arxiv_id":"2405.10853","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-large-language-model-meets-optimization","title":"When Large Language Model Meets Optimization","date":"2024-05-16","arxiv_id":"2405.10098","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-bias-mitigation-from-the","title":"Large Language Model Bias Mitigation from the Perspective of Knowledge Editing","date":"2024-05-15","arxiv_id":"2405.09341","repositories_listed":0,"syntology":null},{"url":null,"slug":"word-alignment-as-preference-for-machine","title":"Word Alignment as Preference for Machine Translation","date":"2024-05-15","arxiv_id":"2405.09223","repositories_listed":0,"syntology":null},{"url":null,"slug":"assisted-debate-builder-with-large-language","title":"Assisted Debate Builder with Large Language Models","date":"2024-05-14","arxiv_id":"2405.13015","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-repair-of-ai-code-with-large","title":"Automated Repair of AI Code with Large Language Models and Formal Verification","date":"2024-05-14","arxiv_id":"2405.08848","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-threat-intelligence-at-the-edge","title":"Distributed Threat Intelligence at the Edge Devices: A Large Language Model-Driven Approach","date":"2024-05-14","arxiv_id":"2405.08755","repositories_listed":0,"syntology":null}],"record_sha256":"52b26b19228b2d70c546572db798f5e7af6a2ce14a0c708135a5641c05b66cc5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}