8 citations · 10 across the 10 of their papers we have counts for
10 papers
Divide-Fuse-Conquer: Eliciting "Aha Moments" in Multi-Scenario Games
Xiaoqing Zhang, Huabin Zheng, Ang Lv +5
Large language models (LLMs) have been observed to suddenly exhibit advanced reasoning abilities during reinforcement learning (RL), resembling an ``aha moment'' triggered by simpl…
ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models
Zirui Song, Guangxian Ouyang, Mingzhe Li +10
Large Vision-Language Models (LVLMs) have recently advanced robotic manipulation by leveraging vision for scene perception and language for instruction following. However, existing…
The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake News
Yuhan Liu, Yuxuan Liu, Xiaoqing Zhang +2
In today's digital environment, the rapid propagation of fake news via social networks poses significant social challenges. Most existing detection methods either employ traditiona…
Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement
Xiaoqing Zhang, Yuhan Liu, Flood Sung +3
Code generation is crucial in software engineering for automating the coding process efficiently. While test-time computation methods show promise, they suffer from high latency du…
More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
Xiaoqing Zhang, Ang Lv, Yuhan Liu +6
Large language models (LLMs) excel at few-shot in-context learning (ICL) without requiring parameter updates. However, as ICL demonstrations increase from a few to many, performanc…
A Large-scale Time-aware Agents Simulation for Influencer Selection in Digital Advertising Campaigns
Xiaoqing Zhang, Xiuying Chen, Yuhan Liu +3
In the digital world, influencers are pivotal as opinion leaders, shaping the views and choices of their influencees. Modern advertising often follows this trend, where marketers c…
The Stepwise Deception: Simulating the Evolution from True News to Fake News with LLM Agents
Yuhan Liu, Zirui Song, Juntian Zhang +3
With the growing spread of misinformation online, understanding how true news evolves into fake news has become crucial for early detection and prevention. However, previous resear…
Selecting Query-bag as Pseudo Relevance Feedback for Information-seeking Conversations
Xiaoqing Zhang, Xiuying Chen, Shen Gao +4
Information-seeking dialogue systems are widely used in e-commerce systems, with answers that must be tailored to fit the specific settings of the online system. Given the user que…
SAGraph: A Large-Scale Social Graph Dataset with Comprehensive Context for Influencer Selection in Marketing
Xiaoqing Zhang, Yuhan Liu, Jianzhou Wang +3
Influencer marketing campaign success heavily depends on identifying key opinion leaders who can effectively leverage their credibility and reach to promote products or services. T…
From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News
Yuhan Liu, Xiuying Chen, Xiaoqing Zhang +3
In the digital era, the rapid propagation of fake news and rumors via social networks brings notable societal challenges and impacts public opinion regulation. Traditional fake new…