activity
20232026
most citedLarge Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey

12 citations · 16 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8

Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…

cs.CL2026

Large Language Model Agents Are Not Always Faithful Self-Evolvers

Weixiang Zhao, Yingshuo Wang, Yichen Zhang +5

Self-evolving large language model (LLM) agents continually improve by accumulating and reusing past experience, yet it remains unclear whether they faithfully rely on that experie…

cs.AI2025

Exploring and Exploiting the Inherent Efficiency within Large Reasoning Models for Self-Guided Efficiency Enhancement

Weixiang Zhao, Jiahe Guo, Yang Deng +7

Recent advancements in large reasoning models (LRMs) have significantly enhanced language models' capabilities in complex problem-solving by emulating human-like deliberative think…

cs.CL2025

When Less Language is More: Language-Reasoning Disentanglement Makes LLMs Better Multilingual Reasoners

Weixiang Zhao, Jiahe Guo, Yang Deng +9

Multilingual reasoning remains a significant challenge for large language models (LLMs), with performance disproportionately favoring high-resource languages. Drawing inspiration f…

cs.AI2025★ 1 cited

Trade-offs in Large Reasoning Models: An Empirical Analysis of Deliberative and Adaptive Reasoning over Foundational Capabilities

Weixiang Zhao, Xingyu Sui, Jiahe Guo +9

Recent advancements in Large Reasoning Models (LRMs), such as OpenAI's o1/o3 and DeepSeek-R1, have demonstrated remarkable performance in specialized reasoning tasks through human-…

cs.CL2024

Lens: Rethinking Multilingual Enhancement for Large Language Models

Weixiang Zhao, Yulin Hu, Jiahe Guo +7

As global demand for multilingual large language models (LLMs) grows, most LLMs still remain overly focused on English, leading to the limited access to advanced AI for non-English…

cs.CL2024★ 12 cited

Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey

Hao Yang, Yanyan Zhao, Yang Wu +6

Compared to traditional sentiment analysis, which only considers text, multimodal sentiment analysis needs to consider emotional signals from multimodal sources simultaneously and…

cs.CL2024

SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models

Weixiang Zhao, Shilong Wang, Yulin Hu +6

The continual learning (CL) ability is vital for deploying large language models (LLMs) in the dynamic world. Existing methods devise the learning module to acquire task-specific k…

cs.CL2023★ 3 cited

Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue

Yuanxing Liu, Wei-Nan Zhang, Yifan Chen +6

E-commerce pre-sales dialogue aims to understand and elicit user needs and preferences for the items they are seeking so as to provide appropriate recommendations. Conversational r…