28 citations · 87 across the 29 of their papers we have counts for
6 papers · 1 filter
MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh +8
Large Language Models (LLMs) are becoming essential tools for various natural language processing tasks but often suffer from generating outdated or incorrect information. Retrieva…
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion
Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang +8
Ensuring the security of released large language models (LLMs) poses a significant dilemma, as existing mechanisms either compromise ownership rights or raise data privacy concerns…
Assessing and Enhancing Large Language Models in Rare Disease Question-answering
Guanchu Wang, Junhao Ran, Ruixiang Tang +6
Despite the impressive capabilities of Large Language Models (LLMs) in general medical domains, questions remain about their performance in diagnosing rare diseases. To answer this…
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches
Jiayi Yuan, Hongyi Liu, Shaochen Zhong +9
Long context capability is a crucial competency for large language models (LLMs) as it mitigates the human struggle to digest long-form texts. This capability enables complex task-…
LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting
Yu-Neng Chuang, Songchen Li, Jiayi Yuan +11
Time Series Forecasting (TSF) has long been a challenge in time series analysis. Inspired by the success of Large Language Models (LLMs), researchers are now developing Large Time…
FaithLM: Towards Faithful Explanations for Large Language Models
Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang +7
Large language models (LLMs) increasingly produce natural language explanations, yet these explanations often lack faithfulness, and they do not reliably reflect the evidence the m…