MetaLint: Generalizable Idiomatic Code Quality Analysis through Instruction-Following and Easy-to-Hard Generalization
arXiv:2507.11687v1 Announce Type: cross Abstract: Large Language Models, though successful in code generation, struggle with code quality analysis because they ...
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[2403.15740] Protecting Copyrighted Material with Unique Identifiers in Large Language Model Training
[Submitted on 23 Mar 2024 (v1), last revised 16 Jul 2025 (this version, v3)] View a PDF of the paper ...
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Learning from Emotional Dialogues and Psychological Texts with Student-Centered Evaluation
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals ...
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A Streamlined Framework for Enhancing LLM Reasoning with Agentic Tools
[Submitted on 7 Feb 2025 (v1), last revised 14 Jul 2025 (this version, v2)] View a PDF of the paper ...
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Evaluating LLM Safety in Kazakh-Russian Bilingual Contexts
[Submitted on 19 Feb 2025 (v1), last revised 14 Jul 2025 (this version, v2)] Authors:Maiya Goloburda, Nurkhan Laiyk, Diana Turmakhan, ...
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MedicalBERT: enhancing biomedical natural language processing using pretrained BERT-based model
arXiv:2507.08013v1 Announce Type: new Abstract: Recent advances in natural language processing (NLP) have been driven bypretrained language models like BERT, ...
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[2507.08529] A Multi-granularity Concept Sparse Activation and Hierarchical Knowledge Graph Fusion Framework for Rare Disease Diagnosis
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals ...
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Prompt Perturbations Reveal Human-Like Biases in LLM Survey Responses
arXiv:2507.07188v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as proxies for human subjects in social science ...
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[2504.02670] Affordable AI Assistants with Knowledge Graph of Thoughts
[Submitted on 3 Apr 2025 (v1), last revised 10 Jul 2025 (this version, v5)] Authors:Maciej Besta, Lorenzo Paleari, Jia Hao ...
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Scaling Towards the Information Boundary of Instruction Set: InfinityInstruct-Subject Technical Report
arXiv:2507.06968v1 Announce Type: cross Abstract: Instruction tuning has become a foundation for unlocking the capabilities of large-scale pretrained models and ...
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