activity
20232025
most citedThought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Bootstrapped Prolog-based Chain-of-Thought

4 citations · 9 across the 9 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.LG2024★ 2 cited

Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural Interaction

Xiaoyu Tan, Yongxin Deng, Chao Qu +4

Recently, models for user representation learning have been widely applied in click-through-rate (CTR) and conversion-rate (CVR) prediction. Usually, the model learns a universal u…

cs.CL2024★ 1 cited

CogniDual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks

Yongxin Deng, Xihe Qiu, Xiaoyu Tan +5

Cognitive psychology investigates perception, attention, memory, language, problem-solving, decision-making, and reasoning. Kahneman's dual-system theory elucidates the human decis…

cs.AI2024★ 4 cited

Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Bootstrapped Prolog-based Chain-of-Thought

Xiaoyu Tan, Yongxin Deng, Xihe Qiu +7

Large language models have demonstrated remarkable capabilities as general-purpose assistants, excelling in a wide range of reasoning tasks and supporting various aspects of daily…

cs.CL2024★ 1 cited

Towards Collaborative Intelligence: Propagating Intentions and Reasoning for Multi-Agent Coordination with Large Language Models

Xihe Qiu, Haoyu Wang, Xiaoyu Tan +6

Effective collaboration in multi-agent systems requires communicating goals and intentions between agents. Current agent frameworks often suffer from dependencies on single-agent e…

cs.RO2024

Subequivariant Reinforcement Learning Framework for Coordinated Motion Control

Haoyu Wang, Xiaoyu Tan, Xihe Qiu +1

Effective coordination is crucial for motion control with reinforcement learning, especially as the complexity of agents and their motions increases. However, many existing methods…