4 papers
On the Effect of Sampling Diversity in Scaling LLM Inference
Tianchun Wang, Zichuan Liu, Yuanzhou Chen +5
Large language model (LLM) scaling inference is key to unlocking greater performance, and leveraging diversity has proven an effective way to enhance it. Motivated by the observed…
Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Models
Zhawnen Chen, Tianchun Wang, Yizhou Wang +4
Can large multimodal models have a human-like ability for emotional and social reasoning, and if so, how does it work? Recent research has discovered emergent theory-of-mind (ToM)…
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
Tianchun Wang, Yuanzhou Chen, Zichuan Liu +4
The advent of large language models (LLMs) has revolutionized the field of text generation, producing outputs that closely mimic human-like writing. Although academic and industria…
Protecting Your LLMs with Information Bottleneck
Zichuan Liu, Zefan Wang, Linjie Xu +6
The advent of large language models (LLMs) has revolutionized the field of natural language processing, yet they might be attacked to produce harmful content. Despite efforts to et…