{"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-modeling/papers/90","list_of":"/task/language-modeling","task":"Language Modeling","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":90,"pages_in_order":142,"rows_per_page":100,"rows":[8901,9000],"of":14182,"counts":{"archive_papers_tagged":14182,"with_a_code_link":5620,"where_syntology_ran_a_sample":1894,"not_listed_spam_title":0,"listed":14182,"listed_where_code_ran":1894,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1580,"every_run_a_failure_of_syntologys_instrument":314,"listed_with_a_run_with_no_instrument_failure":1580,"listed_every_run_a_failure_of_syntologys_instrument":314,"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-modeling","prev":"/task/language-modeling/papers/89","next":"/task/language-modeling/papers/91","papers":[{"url":null,"slug":"knowledge-distillation-vs-pretraining-from","title":"Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget","date":"2024-04-30","arxiv_id":"2404.19319","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-agent-for-fake-news","title":"Large Language Model Agent for Fake News Detection","date":"2024-04-30","arxiv_id":"2405.01593","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-informed-patent-image","title":"Large Language Model Informed Patent Image Retrieval","date":"2024-04-30","arxiv_id":"2404.19360","repositories_listed":0,"syntology":null},{"url":null,"slug":"mix-of-experts-language-model-for-named","title":"Mix of Experts Language Model for Named Entity Recognition","date":"2024-04-30","arxiv_id":"2404.19192","repositories_listed":0,"syntology":null},{"url":null,"slug":"more-compute-is-what-you-need","title":"More Compute Is What You Need","date":"2024-04-30","arxiv_id":"2404.19484","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-n-gram-models-their-impact-in","title":"Revisiting N-Gram Models: Their Impact in Modern Neural Networks for Handwritten Text Recognition","date":"2024-04-30","arxiv_id":"2404.19317","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-framework-for-real-time-safeguarding-the","title":"A Framework for Real-time Safeguarding the Text Generation of Large Language Model","date":"2024-04-29","arxiv_id":"2404.19048","repositories_listed":0,"syntology":null},{"url":null,"slug":"anywhere-a-multi-agent-framework-for-reliable","title":"Anywhere: A Multi-Agent Framework for User-Guided, Reliable, and Diverse Foreground-Conditioned Image Generation","date":"2024-04-29","arxiv_id":"2404.18598","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecc-analyzer-extract-trading-signal-from","title":"ECC Analyzer: Extract Trading Signal from Earnings Conference Calls using Large Language Model for Stock Performance Prediction","date":"2024-04-29","arxiv_id":"2404.18470","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-interactive-image-retrieval-with","title":"Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Models","date":"2024-04-29","arxiv_id":"2404.18746","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-automatic-text-recognition-with","title":"Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library","date":"2024-04-29","arxiv_id":"2404.18722","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixture-of-instructions-comprehensive","title":"Mixture-of-Instructions: Comprehensive Alignment of a Large Language Model through the Mixture of Diverse System Prompting Instructions","date":"2024-04-29","arxiv_id":"2404.18410","repositories_listed":0,"syntology":null},{"url":null,"slug":"plan-of-thoughts-heuristic-guided-problem","title":"Plan of Thoughts: Heuristic-Guided Problem Solving with Large Language Models","date":"2024-04-29","arxiv_id":"2404.19055","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplifying-multimodality-unimodal-approach","title":"Simplifying Multimodality: Unimodal Approach to Multimodal Challenges in Radiology with General-Domain Large Language Model","date":"2024-04-29","arxiv_id":"2405.01591","repositories_listed":0,"syntology":null},{"url":null,"slug":"bias-neutralization-framework-measuring","title":"Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)","date":"2024-04-28","arxiv_id":"2404.18276","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-perplexity-predict-fine-tuning","title":"Can Perplexity Predict Fine-Tuning Performance? An Investigation of Tokenization Effects on Sequential Language Models for Nepali","date":"2024-04-28","arxiv_id":"2404.18071","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextual-spelling-correction-with-language","title":"Contextual Spelling Correction with Language Model for Low-resource Setting","date":"2024-04-28","arxiv_id":"2404.18072","repositories_listed":0,"syntology":null},{"url":null,"slug":"mmac-copilot-multi-modal-agent-collaboration","title":"MMAC-Copilot: Multi-modal Agent Collaboration Operating Copilot","date":"2024-04-28","arxiv_id":"2404.18074","repositories_listed":0,"syntology":null},{"url":null,"slug":"patentgpt-a-large-language-model-for","title":"PatentGPT: A Large Language Model for Intellectual Property","date":"2024-04-28","arxiv_id":"2404.18255","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-and-transformer","title":"Transfer Learning and Transformer Architecture for Financial Sentiment Analysis","date":"2024-04-28","arxiv_id":"2405.01586","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-large-language-models-for","title":"Utilizing Large Language Models for Information Extraction from Real Estate Transactions","date":"2024-04-28","arxiv_id":"2404.18043","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-vision-language-pre-training-for","title":"Medical Vision-Language Pre-Training for Brain Abnormalities","date":"2024-04-27","arxiv_id":"2404.17779","repositories_listed":0,"syntology":null},{"url":null,"slug":"recall-retrieve-and-reason-towards-better-in","title":"Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction","date":"2024-04-27","arxiv_id":"2404.17809","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaffold-bpe-enhancing-byte-pair-encoding","title":"Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal","date":"2024-04-27","arxiv_id":"2404.17808","repositories_listed":0,"syntology":null},{"url":null,"slug":"serpent-vlm-self-refining-radiology-report","title":"SERPENT-VLM : Self-Refining Radiology Report Generation Using Vision Language Models","date":"2024-04-27","arxiv_id":"2404.17912","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-enhanced-single-choice","title":"Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering","date":"2024-04-27","arxiv_id":"2404.17949","repositories_listed":0,"syntology":null},{"url":null,"slug":"vaner-leveraging-large-language-model-for","title":"VANER: Leveraging Large Language Model for Versatile and Adaptive Biomedical Named Entity Recognition","date":"2024-04-27","arxiv_id":"2404.17835","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-model-agent-as-a-mechanical","title":"Large Language Model Agent as a Mechanical Designer","date":"2024-04-26","arxiv_id":"2404.17525","repositories_listed":0,"syntology":null},{"url":null,"slug":"ruffle-riley-insights-from-designing-and","title":"Ruffle&Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System","date":"2024-04-26","arxiv_id":"2404.17460","repositories_listed":0,"syntology":null},{"url":null,"slug":"player-driven-emergence-in-llm-driven-game","title":"Player-Driven Emergence in LLM-Driven Game Narrative","date":"2024-04-25","arxiv_id":"2404.17027","repositories_listed":0,"syntology":null},{"url":null,"slug":"prefix-text-as-a-yarn-eliciting-non-english","title":"Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model","date":"2024-04-25","arxiv_id":"2404.16766","repositories_listed":0,"syntology":null},{"url":null,"slug":"tele-flm-technical-report","title":"Tele-FLM Technical Report","date":"2024-04-25","arxiv_id":"2404.16645","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-gpt-surprise-offering-large-language","title":"The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances","date":"2024-04-25","arxiv_id":"2407.09975","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-evaluating-large","title":"A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industry","date":"2024-04-24","arxiv_id":"2404.15777","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-esm2-graph-enhanced-protein-sequence","title":"Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering","date":"2024-04-24","arxiv_id":"2404.15805","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-conceptual-abstraction-in-llms","title":"Detecting Conceptual Abstraction in LLMs","date":"2024-04-24","arxiv_id":"2404.15848","repositories_listed":0,"syntology":null},{"url":null,"slug":"fusion-of-domain-adapted-vision-and-language","title":"Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering","date":"2024-04-24","arxiv_id":"2404.16192","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-measures-for-zero-shot-cross","title":"Generalization Measures for Zero-Shot Cross-Lingual Transfer","date":"2024-04-24","arxiv_id":"2404.15928","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequence-can-secretly-tell-you-what-to","title":"CORM: Cache Optimization with Recent Message for Large Language Model Inference","date":"2024-04-24","arxiv_id":"2404.15949","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-efficient-patient-recruitment-for","title":"Towards Efficient Patient Recruitment for Clinical Trials: Application of a Prompt-Based Learning Model","date":"2024-04-24","arxiv_id":"2404.16198","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-artificial-intelligence-to-unlock","title":"Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses","date":"2024-04-24","arxiv_id":"2407.09480","repositories_listed":0,"syntology":null},{"url":null,"slug":"breaking-walls-pioneering-automatic-speech","title":"Breaking Walls: Pioneering Automatic Speech Recognition for Central Kurdish: End-to-End Transformer Paradigm","date":"2024-04-23","arxiv_id":"2406.02561","repositories_listed":0,"syntology":null},{"url":null,"slug":"ct-agent-clinical-trial-multi-agent-with","title":"ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning","date":"2024-04-23","arxiv_id":"2404.14777","repositories_listed":0,"syntology":null},{"url":null,"slug":"llm-enhanced-causal-discovery-in-temporal","title":"RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model","date":"2024-04-23","arxiv_id":"2404.14786","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-large-language-model-is-a-human","title":"Multimodal Large Language Model is a Human-Aligned Annotator for Text-to-Image Generation","date":"2024-04-23","arxiv_id":"2404.15100","repositories_listed":0,"syntology":null},{"url":null,"slug":"pegasus-v1-technical-report","title":"Pegasus-v1 Technical Report","date":"2024-04-23","arxiv_id":"2404.14687","repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-augmented-generation-for-domain","title":"Retrieval Augmented Generation for Domain-specific Question Answering","date":"2024-04-23","arxiv_id":"2404.14760","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-delta-generator-with-large-multi-modal","title":"Visual Delta Generator with Large Multi-modal Models for Semi-supervised Composed Image Retrieval","date":"2024-04-23","arxiv_id":"2404.15516","repositories_listed":0,"syntology":null},{"url":null,"slug":"xc-cache-cross-attending-to-cached-context","title":"XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference","date":"2024-04-23","arxiv_id":"2404.15420","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multimodal-automated-interpretability-agent","title":"A Multimodal Automated Interpretability Agent","date":"2024-04-22","arxiv_id":"2404.14394","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-llm-to-nmt-advancing-low-resource","title":"From LLM to NMT: Advancing Low-Resource Machine Translation with Claude","date":"2024-04-22","arxiv_id":"2404.13813","repositories_listed":0,"syntology":null},{"url":null,"slug":"paramanu-ganita-language-model-with","title":"PARAMANU-GANITA: Language Model with Mathematical Capabilities","date":"2024-04-22","arxiv_id":"2404.14395","repositories_listed":0,"syntology":null},{"url":"/paper/phi-3-technical-report-a-highly-capable","slug":"phi-3-technical-report-a-highly-capable","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","date":"2024-04-22","arxiv_id":"2404.14219","repositories_listed":0,"syntology":null},{"url":null,"slug":"pixels-and-predictions-potential-of-gpt-4v-in","title":"Pixels and Predictions: Potential of GPT-4V in Meteorological Imagery Analysis and Forecast Communication","date":"2024-04-22","arxiv_id":"2404.15166","repositories_listed":0,"syntology":null},{"url":null,"slug":"q-tuning-queue-based-prompt-tuning-for","title":"Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning","date":"2024-04-22","arxiv_id":"2404.14607","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-role-of-ffns-in-driving","title":"Understanding the role of FFNs in driving multilingual behaviour in LLMs","date":"2024-04-22","arxiv_id":"2404.13855","repositories_listed":0,"syntology":null},{"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":"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":"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":"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":"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":"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":"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":"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":"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":"legalpro-bert-classification-of-legal","title":"LegalPro-BERT: Classification of Legal Provisions by fine-tuning BERT Large Language Model","date":"2024-04-15","arxiv_id":"2404.10097","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":"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":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}],"record_sha256":"4a80dcc01caf1858a9f1acab7c5d4ace2cd447974d5fb865736b77d82a50c203","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}