15 citations · 44 across the 17 of their papers we have counts for
6 papers · 1 filter
GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation
Fei Tang, Yongliang Shen, Hang Zhang +6
Large language model-based explainable recommendation (LLM-based ER) systems show promise in generating human-like explanations for recommendations. However, they face challenges i…
EgoSocialArena: Benchmarking the Social Intelligence of Large Language Models from a First-person Perspective
Guiyang Hou, Wenqi Zhang, Yongliang Shen +3
Social intelligence is built upon three foundational pillars: cognitive intelligence, situational intelligence, and behavioral intelligence. As large language models (LLMs) become…
Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Wenqi Zhang, Zhenglin Cheng, Yuanyu He +8
Although most current large multimodal models (LMMs) can already understand photos of natural scenes and portraits, their understanding of abstract images, e.g., charts, maps, or l…
Advancing Process Verification for Large Language Models via Tree-Based Preference Learning
Mingqian He, Yongliang Shen, Wenqi Zhang +2
Large Language Models (LLMs) have demonstrated remarkable potential in handling complex reasoning tasks by generating step-by-step rationales.Some methods have proven effective in…
Information Re-Organization Improves Reasoning in Large Language Models
Xiaoxia Cheng, Zeqi Tan, Wei Xue +1
Improving the reasoning capabilities of large language models (LLMs) has attracted considerable interest. Recent approaches primarily focus on improving the reasoning process to yi…
Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization
Wenqi Zhang, Ke Tang, Hai Wu +7
Large Language Models (LLMs) exhibit robust problem-solving capabilities for diverse tasks. However, most LLM-based agents are designed as specific task solvers with sophisticated…