9 papers
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…
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…
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…
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…
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…
VeritasFi: An Adaptable, Multi-tiered RAG Framework for Multi-modal Financial Question Answering
Zhenghan Tai, Hanwei Wu, Qingchen Hu +24
Retrieval-Augmented Generation (RAG) is becoming increasingly essential for Question Answering (QA) in the financial sector, where accurate and contextually grounded insights from…