2 citations · 4 across the 24 of their papers we have counts for
16 papers · 1 filter
Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework
Chenyuan Zhang, Qiguang Chen, Xie Chen +6
Cross-lingual chain-of-thought (XCoT) with self-consistency markedly enhances multilingual reasoning, yet existing methods remain costly due to extensive sampling of full trajector…
Learning the Boundary of Solvability: Aligning LLMs to Detect Unsolvable Problems
Dengyun Peng, Qiguang Chen, Bofei Liu +6
Ensuring large language model (LLM) reliability requires distinguishing objective unsolvability (inherent contradictions) from subjective capability limitations (tasks exceeding mo…
The Molecular Structure of Thought: Mapping the Topology of Long Chain-of-Thought Reasoning
Qiguang Chen, Yantao Du, Ziniu Li +10
Large language models (LLMs) often fail to learn effective long chain-of-thought (Long CoT) reasoning from human or non-Long-CoT LLMs imitation. To understand this, we propose that…
Beware of Reasoning Overconfidence: Pitfalls in the Reasoning Process for Multi-solution Tasks
Jiannan Guan, Qiguang Chen, Libo Qin +5
Large Language Models (LLMs) excel in reasoning tasks requiring a single correct answer, but they perform poorly in multi-solution tasks that require generating comprehensive and d…
MAC-SLU: Multi-Intent Automotive Cabin Spoken Language Understanding Benchmark
Yuezhang Peng, Chonghao Cai, Ziang Liu +10
Spoken Language Understanding (SLU), which aims to extract user semantics to execute downstream tasks, is a crucial component of task-oriented dialog systems. Existing SLU datasets…
The Universal Landscape of Human Reasoning
Qiguang Chen, Jinhao Liu, Libo Qin +14
Understanding how information is dynamically accumulated and transformed in human reasoning has long challenged cognitive psychology, philosophy, and artificial intelligence. Exist…
COIG-Writer: A High-Quality Dataset for Chinese Creative Writing with Thought Processes
Yunwen Li, Shuangshuang Ying, Xingwei Qu +16
Large language models exhibit systematic deficiencies in creative writing, particularly in non-English contexts where training data is scarce and lacks process-level supervision. W…
Beyond Correctness: Evaluating Subjective Writing Preferences Across Cultures
Shuangshuang Ying, Yunwen Li, Xingwei Qu +21
Current preference learning methods achieve high accuracy on standard benchmarks but exhibit significant performance degradation when objective quality signals are removed. We intr…
Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks
Wenbo Pan, Jie Xu, Qiguang Chen +5
Large Language Models (LLMs) should refuse to answer questions beyond their knowledge. This capability, which we term knowledge-aware refusal, is crucial for factual reliability, w…
X-WebAgentBench: A Multilingual Interactive Web Benchmark for Evaluating Global Agentic System
Peng Wang, Ruihan Tao, Qiguang Chen +2
Recently, large language model (LLM)-based agents have achieved significant success in interactive environments, attracting significant academic and industrial attention. Despite t…
RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning
Qiguang Chen, Libo Qin, Jinhao Liu +4
Chain-of-Thought (CoT) reasoning has proven effective in enhancing large language models (LLMs) on complex tasks, spurring research into its underlying mechanisms. However, two pri…
DLPO: Towards a Robust, Efficient, and Generalizable Prompt Optimization Framework from a Deep-Learning Perspective
Dengyun Peng, Yuhang Zhou, Qiguang Chen +3
Large Language Models (LLMs) have achieved remarkable success across diverse tasks, largely driven by well-designed prompts. However, crafting and selecting such prompts often requ…
Unlocking the Capabilities of Thought: A Reasoning Boundary Framework to Quantify and Optimize Chain-of-Thought
Qiguang Chen, Libo Qin, Jiaqi Wang +2
Chain-of-Thought (CoT) reasoning has emerged as a promising approach for enhancing the performance of large language models (LLMs) on complex reasoning tasks. Recently, a series of…
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration
Libo Qin, Qiguang Chen, Hao Fei +3
Recently, rapid advancements in Multi-Modal In-Context Learning (MM-ICL) have achieved notable success, which is capable of achieving superior performance across various tasks with…
Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong Information
Yongheng Zhang, Qiguang Chen, Jingxuan Zhou +5
Chain-of-Thought (CoT) has become a vital technique for enhancing the performance of Large Language Models (LLMs), attracting increasing attention from researchers. One stream of a…
What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices
Zhi Chen, Qiguang Chen, Libo Qin +7
Recent advancements in large language models (LLMs) with extended context windows have significantly improved tasks such as information extraction, question answering, and complex…