1 citations · 1 across the 5 of their papers we have counts for
5 papers
RPS: Information Elicitation with Reinforcement Prompt Selection
Tao Wang, Jingyao Lu, Xibo Wang +5
Large language models (LLMs) have shown remarkable capabilities in dialogue generation and reasoning, yet their effectiveness in eliciting user-known but concealed information in o…
From Perception to Action: An Interactive Benchmark for Vision Reasoning
Yuhao Wu, Maojia Song, Yihuai Lan +8
Understanding the physical structure is essential for real-world applications such as embodied agents, interactive design, and long-horizon manipulation. Yet, prevailing Vision-Lan…
FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
Fatema Siddika, Md Anwar Hossen, J. Pablo Muñoz +3
Parameter-efficient fine-tuning (PEFT) adapts large pre-trained models by updating only a small subset of parameters. Recently, Representation Fine-Tuning (ReFT) has emerged as an…
All in an Aggregated Image for In-Image Learning
Lei Wang, Wanyu Xu, Zhiqiang Hu +5
This paper introduces a new in-context learning (ICL) mechanism called In-Image Learning (IL) that combines demonstration examples, visual cues, and chain-of-thought reasoning…
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay
Yihuai Lan, Zhiqiang Hu, Lei Wang +6
This paper explores the open research problem of understanding the social behaviors of LLM-based agents. Using Avalon as a testbed, we employ system prompts to guide LLM agents in…