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arXiv:2603.14217v1 Announce Type: new Abstract: In cognitive science and linguistic theory, dialogue is not seen as a chain of independent utterances but rather as a …
arXiv:2603.14239v1 Announce Type: new Abstract: SystemVerilog Assertions (SVAs) are crucial for hardware verification. Recent studies leverage general-purpose LLMs to translate natural language properties to SVAs …
arXiv:2603.14251v1 Announce Type: new Abstract: Large Reasoning Language Models (LRLMs) demonstrate impressive capabilities on complex tasks by utilizing long Chain-of-Thought reasoning. However, they are prone …
arXiv:2603.14257v1 Announce Type: new Abstract: Existing automatic scientific question generation studies mainly focus on single-document factoid QA, overlooking the inter-document reasoning crucial for scientific understanding. …
arXiv:2603.14265v1 Announce Type: new Abstract: Recent advances in Retrieval-Augmented Generation (RAG) have enabled large language models (LLMs) to ground outputs in clinical evidence. However, connecting …
arXiv:2603.14303v1 Announce Type: new Abstract: Existing KV cache compression methods generally operate on discrete tokens or non-semantic chunks. However, such approaches often lead to semantic …
arXiv:2603.14313v1 Announce Type: new Abstract: Federal Open Market Committee (FOMC) statements are a major source of monetary-policy information, and even subtle changes in their wording …
arXiv:2603.14347v1 Announce Type: new Abstract: Motivation is a central driver of human behavior, shaping decisions, goals, and task performance. As large language models (LLMs) become …
arXiv:2603.14355v1 Announce Type: new Abstract: Safety tuning through supervised fine-tuning and reinforcement learning from human feedback has substantially improved the robustness of large language models …
arXiv:2603.14400v1 Announce Type: new Abstract: The minimal pairs paradigm of comparing model probabilities for contrasting completions has proven useful for evaluating linguistic knowledge in language …
arXiv:2603.14410v1 Announce Type: new Abstract: Generating long-form linear fiction from open-ended themes remains a major challenge for large language models, which frequently fail to guarantee …
arXiv:2603.14430v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following …