27 citations · 27 across the 6 of their papers we have counts for
4 papers · 1 filter
Do Multimodal LLMs See Before They Read? Diagnosing Contextual Sycophancy
Yi-Cheng Lai, Hen-Hsen Huang
External text can override conflicting image evidence in multimodal large language models, a failure we call multimodal contextual sycophancy. We introduce a 998-case diagnostic th…
AR: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models
Cheng-Kai Yeh, Hsing-Wang Lee, Chung-Hung Kuo +1
Abstraction--the ability to recognize and distill essential computational patterns from complex problem statements--is a foundational skill in computer science, critical both for h…
Efficient Beam Search for Large Language Models Using Trie-Based Decoding
Brian J Chan, MaoXun Huang, Jui-Hung Cheng +2
This work presents a novel trie (prefix-tree)-based parallel decoding method that addresses the memory inefficiency of batch-based beam search. By sharing a single KV cache across…
Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks
Brian J Chan, Chao-Ting Chen, Jui-Hung Cheng +1
Retrieval-augmented generation (RAG) has gained traction as a powerful approach for enhancing language models by integrating external knowledge sources. However, RAG introduces cha…