5 papers
Assessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers
Samuel Schapiro, Alexi Gladstone, Jonah Black +1
Measuring the creativity of large language models (LLMs) is essential for designing methods that can improve creativity and for enhancing our scientific understanding of this abili…
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Zhaochen Su, Peng Xia, Hangyu Guo +12
Recent progress in multimodal reasoning has been significantly advanced by textual Chain-of-Thought (CoT), a paradigm where models conduct reasoning within language. This text-cent…
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…
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…