3 citations · 7 across the 10 of their papers we have counts for
11 papers
Training LLM Agents for Spontaneous, Reward-Free Self-Evolution via World Knowledge Exploration
Qifan Zhang, Dongyang Ma, Tianqing Fang +5
Most agents today ``self-evolve'' by following rewards and rules defined by humans. However, this process remains fundamentally dependent on external supervision; without human gui…
Exposing Weaknesses of Large Reasoning Models through Graph Algorithm Problems
Qifan Zhang, Jianhao Ruan, Aochuan Chen +4
Large Reasoning Models (LRMs) have advanced rapidly; however, existing benchmarks in mathematics, code, and common-sense reasoning remain limited. They lack long-context evaluation…
Incentivizing In-depth Reasoning over Long Contexts with Process Advantage Shaping
Miao Peng, Weizhou Shen, Nuo Chen +3
Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective in enhancing LLMs short-context reasoning, but its performance degrades in long-context scenarios that re…
Is AI mingling or bullying me? Exploring User Interactions with a Chatbot in China
Nuo Chen, Pu Yan, Jia Li +1
Since its viral emergence in early 2024, Comment Robert-a Weibo-launched social chatbot-has gained widespread attention on the Chinese Internet for its unsolicited and unpredictabl…
How does Misinformation Affect Large Language Model Behaviors and Preferences?
Miao Peng, Nuo Chen, Jianheng Tang +1
Large Language Models (LLMs) have shown remarkable capabilities in knowledge-intensive tasks, while they remain vulnerable when encountering misinformation. Existing studies have e…
Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners
Miao Peng, Nuo Chen, Zongrui Suo +1
Despite significant advancements in Large Language Models (LLMs), developing advanced reasoning capabilities in LLMs remains a key challenge. Process Reward Models (PRMs) have demo…
ControlMath: Controllable Data Generation Promotes Math Generalist Models
Nuo Chen, Ning Wu, Jianhui Chang +1
Utilizing large language models (LLMs) for data augmentation has yielded encouraging results in mathematical reasoning. However, these approaches face constraints in problem divers…
The Oscars of AI Theater: A Survey on Role-Playing with Language Models
Nuo Chen, Yan Wang, Yang Deng +1
This survey explores the burgeoning field of role-playing with language models, focusing on their development from early persona-based models to advanced character-driven simulatio…
Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations
Nuo Chen, Hongguang Li, Juhua Huang +2
Existing retrieval-based methods have made significant strides in maintaining long-term conversations. However, these approaches face challenges in memory database management and a…
Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers
Nuo Chen, Ning Wu, Shining Liang +4
This paper presents an in-depth analysis of Large Language Models (LLMs), focusing on LLaMA, a prominent open-source foundational model in natural language processing. Instead of a…
From Good to Great: Improving Math Reasoning with Tool-Augmented Interleaf Prompting
Nuo Chen, Hongguang Li, Baoyuan Wang +1
This paper investigates the performance of Large Language Models (LLMs) and Tool-augmented LLMs in tackling complex mathematical reasoning tasks. We introduce IMP-TIP: Improving Ma…