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20232026
most citedScaling over Scaling: Exploring Test-Time Scaling Plateau in Large Reasoning Models

1 citations · 3 across the 21 of their papers we have counts for

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15 papers · 1 filter

cs.CL2026

Probing Cultural Awareness in LLMs: A Case Study of Cross-Culture Aesthetic Stylistics

Jiashuo Wang, Fenggang Yu, Jian Wang +6

Large Language Models (LLMs) are increasingly deployed in diverse cultural contexts, yet their ability to master aesthetic stylistics, i.e., the strategic use of language to evoke…

cs.CL2026

Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied Agents

Hanlin Wang, Chak Tou Leong, Jian Wang +1

Recent advancements in large language models (LLMs) have enabled agents to tackle complex embodied tasks through environmental interaction. However, these agents still make subopti…

cs.CL2026

Foresight Optimization for Strategic Reasoning in Large Language Models

Jiashuo Wang, Jiawen Duan, Jian Wang +6

Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-based LLMs to perform effectiv…

cs.CL2026

Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

Youwei Liu, Jian Wang, Hanlin Wang +2

Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act without accessing real environments. Curr…

cs.CL2025

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution

Hanlin Wang, Chak Tou Leong, Jiashuo Wang +2

Reinforcement learning (RL) holds significant promise for training LLM agents to handle complex, goal-oriented tasks that require multi-step interactions with external environments…

cs.CL2025★ 1 cited

Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning

Xinghao Chen, Anhao Zhao, Heming Xia +7

Large Language Models (LLMs) have shown impressive performance on complex tasks through Chain-of-Thought (CoT) reasoning. However, conventional CoT relies on explicitly verbalized…

cs.CL2025

Towards Harmless Multimodal Assistants with Blind Preference Optimization

Yongqi Li, Lu Yang, Jian Wang +3

Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. Given the extensive applications of MLLM…

cs.CL2025

Integrating Chain-of-Thought for Multimodal Alignment: A Study on 3D Vision-Language Learning

Yanjun Chen, Yirong Sun, Xinghao Chen +4

Chain-of-Thought (CoT) reasoning has proven effective in natural language tasks but remains underexplored in multimodal alignment. This study investigates its integration into 3D v…

cs.CL2025

Why Safeguarded Ships Run Aground? Aligned Large Language Models' Safety Mechanisms Tend to Be Anchored in The Template Region

Chak Tou Leong, Qingyu Yin, Jian Wang +1

The safety alignment of large language models (LLMs) remains vulnerable, as their initial behavior can be easily jailbroken by even relatively simple attacks. Since infilling a fix…

cs.CL2025

Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors

Jian Wang, Yinpei Dai, Yichi Zhang +3

Intelligent tutoring agents powered by large language models (LLMs) have been increasingly explored to deliver personalized knowledge in areas such as language learning and science…

cs.CL2024

E2CL: Exploration-based Error Correction Learning for Embodied Agents

Hanlin Wang, Chak Tou Leong, Jian Wang +1

Language models are exhibiting increasing capability in knowledge utilization and reasoning. However, when applied as agents in embodied environments, they often suffer from misali…

cs.CL2024

No Two Devils Alike: Unveiling Distinct Mechanisms of Fine-tuning Attacks

Chak Tou Leong, Yi Cheng, Kaishuai Xu +3

The existing safety alignment of Large Language Models (LLMs) is found fragile and could be easily attacked through different strategies, such as through fine-tuning on a few harmf…

cs.CL2024

Medical Dialogue Generation via Intuitive-then-Analytical Differential Diagnosis

Kaishuai Xu, Wenjun Hou, Yi Cheng +2

Medical dialogue systems have attracted growing research attention as they have the potential to provide rapid diagnoses, treatment plans, and health consultations. In medical dial…

cs.CL2023★ 1 cited

COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goal

Yi Cheng, Wenge Liu, Jian Wang +5

In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond tradition…

cs.CL2023

Self-Detoxifying Language Models via Toxification Reversal

Chak Tou Leong, Yi Cheng, Jiashuo Wang +2

Language model detoxification aims to minimize the risk of generating offensive or harmful content in pretrained language models (PLMs) for safer deployment. Existing methods can b…