most citedLight-IF: Endowing LLMs with Generalizable Reasoning via Preview and Self-Checking for Complex Instruction Following

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cs.CL20251 cited

Light-IF: Endowing LLMs with Generalizable Reasoning via Preview and Self-Checking for Complex Instruction Following

Chenyang Wang, Liang Wen, Shousheng Jia +2

While advancements in the reasoning abilities of LLMs have significantly enhanced their performance in solving mathematical problems, coding tasks, and general puzzles, their effec…

cs.CL2025

Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework

Xiao Wei, Xiaobao Wang, Ning Zhuang +3

Intent detection aims to identify user intents from natural language inputs, where supervised methods rely heavily on labeled in-domain (IND) data and struggle with out-of-domain (…

cs.CL2025

SeedBench: A Multi-task Benchmark for Evaluating Large Language Models in Seed Science

Jie Ying, Zihong Chen, Zhefan Wang +7

Seed science is essential for modern agriculture, directly influencing crop yields and global food security. However, challenges such as interdisciplinary complexity and high costs…

cs.CL2025

PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models

Shi Qiu, Shaoyang Guo, Zhuo-Yang Song +51

Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task oversimplification, data contamination, and flawed e…

cs.CL2025

Consistency of Responses and Continuations Generated by Large Language Models on Social Media

Wentao Xu, Wenlu Fan, Yuqi Zhu +1

Large Language Models (LLMs) demonstrate remarkable capabilities in text generation, yet their emotional consistency and semantic coherence in social media contexts remain insuffic…