7 citations · 8 across the 6 of their papers we have counts for
4 papers · 1 filter
Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Shujin Wu, Cheng Qian, Yi R. Fung +2
The growing capabilities of large language models (LLMs) present a key challenge of maintaining effective human oversight. Weak-to-strong generalization (W2SG) offers a promising f…
The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination
Yuji Zhang, Sha Li, Cheng Qian +8
Hallucination is a persistent challenge in large language models (LLMs), where even with rigorous quality control, models often generate distorted facts. This paradox, in which err…
Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models
Yuji Zhang, Sha Li, Jiateng Liu +5
Hallucination is often regarded as a major impediment for using large language models (LLMs), especially for knowledge-intensive tasks. Even when the training corpus consists solel…
MACAROON: Training Vision-Language Models To Be Your Engaged Partners
Shujin Wu, Yi R. Fung, Sha Li +3
Large vision-language models (LVLMs), while proficient in following instructions and responding to diverse questions, invariably generate detailed responses even when questions are…