activity
20232026
most citedAdapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

18 citations · 26 across the 10 of their papers we have counts for

collaborators

10 papers

cs.AI2026

Is Next-Chunk Reasoning RL Really Better than SFT? Revisiting Training Strategies under no-CoT Data

Yinhao Tang, Youqing Fang, Yanan Sun +8

Recent work proposes next-chunk reasoning RL for leveraging no-CoT data---corpora such as worked solutions and textbook derivations that contain reasoning-rich content but lack exp…

cs.HC2026

MindCopilot: Towards Formalizing and Evaluating Granular Human-LLM Co-Writing

Youqing Fang, Yinhao Tang, Yanan Sun +8

Recent writing assistants are increasingly shifting from passive, prompt-driven interaction to proactive, suggestion-based completion, which integrates localized continuations into…

cs.SE2026★ 6 cited

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Chenyu Zhou, Huacan Chai, Wenteng Chen +18

Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the…

cs.SE2026

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation

Li Hu, Xiuwei Shang, Jieke Shi +6

Deobfuscating binary code remains a fundamental challenge in reverse engineering, as obfuscation is widely used to hinder analysis and conceal program logic. Although large languag…

cs.AI2026

Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation

Weiming Zhang, Jihong Wang, Jiamu Zhou +9

Large Language Models (LLMs) have empowered autonomous agents to handle complex web navigation tasks. While recent studies integrate tree search to enhance long-horizon reasoning,…

cs.CL2026

LogitsCoder: Towards Efficient Chain-of-Thought Path Search via Logits Preference Decoding for Code Generation

Jizheng Chen, Weiming Zhang, Xinyi Dai +6

Code generation remains a challenging task that requires precise and structured reasoning. Existing Test Time Scaling (TTS) methods, including structured tree search, have made pro…

cs.CL2025

LLM4CD: Leveraging Large Language Models for Open-World Knowledge Augmented Cognitive Diagnosis

Weiming Zhang, Lingyue Fu, Qingyao Li +7

Cognitive diagnosis (CD) plays a crucial role in intelligent education, evaluating students' comprehension of knowledge concepts based on their test histories. However, current CD…

cs.CL2025

NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging

Weiming Zhang, Qingyao Li, Xinyi Dai +7

Debugging is a critical aspect of LLM's coding ability. Early debugging efforts primarily focused on code-level analysis, which often falls short when addressing complex programmin…

cs.AI2024★ 18 cited

Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

Qingyao Li, Lingyue Fu, Weiming Zhang +6

Online education platforms, leveraging the internet to distribute education resources, seek to provide convenient education but often fall short in real-time communication with stu…

cs.CL2023★ 2 cited

CodeApex: A Bilingual Programming Evaluation Benchmark for Large Language Models

Lingyue Fu, Huacan Chai, Shuang Luo +13

With the emergence of Large Language Models (LLMs), there has been a significant improvement in the programming capabilities of models, attracting growing attention from researcher…