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cs.CL2026

Instant Personalized Large Language Model Adaptation via Hypernetwork

Zhaoxuan Tan, Zixuan Zhang, Haoyang Wen +8

Personalized large language models (LLMs) tailor content to individual preferences using user profiles or histories. However, existing parameter-efficient fine-tuning (PEFT) method…

cs.CL2026

WeatherArchive-Bench: Benchmarking Retrieval-Augmented Reasoning for Historical Weather Archives

Yongan Yu, Xianda Du, Qingchen Hu +7

Historical archives on weather events are collections of enduring primary source records that offer rich, untapped narratives of how societies have experienced and responded to ext…

cs.CL2026

Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning

Fengran Mo, Yifan Gao, Sha Li +7

Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through natural, multi-turn dialogue. To r…

cs.CL2026

MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues

Zheyuan Liu, Dongwhi Kim, Yixin Wan +4

Multimodal large language models (MLLMs) are increasingly deployed as assistants that interact through text and images, making it crucial to evaluate contextual safety when risk de…

cs.CL2025

WXImpactBench: A Disruptive Weather Impact Understanding Benchmark for Evaluating Large Language Models

Yongan Yu, Qingchen Hu, Xianda Du +3

Climate change adaptation requires the understanding of disruptive weather impacts on society, where large language models (LLMs) might be applicable. However, their effectiveness…

cs.CL2025

FedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models

Chuan Li, Qianyi Zhao, Fengran Mo +1

Efficiently enhancing the reasoning capabilities of large language models (LLMs) in federated learning environments remains challenging, particularly when balancing performance gai…