Author

Bosi Wen

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#natural language process... Preprint Sep 2026

ScopeIF: Improving Scope-Aware Precise Instruction-Following in Large Language Models via Graded Reward Modeling

Precise instruction-following is a fundamental ability of large language models (LLMs), requiring their outputs to strictly satisfy objective constraints in input instructions. In complex application scenarios, these constraints often possess diverse scopes that govern specific response segments rather than the entire...

Bo-Si Wen, Yi-Lin Niu, Xiao-Ying Ning et al. · 0 citations

#artificial intelligence Preprint Sep 2026

From Anomalies to Failures: Constructing Causal Error Graphs for Agentic Trace Diagnosis

CEG-Agent introduces an explicit taxonomy of anomalies, errors, and failures, and constructs Causal Error Graphs (CEGs), a unified typed representation that links execution events, diagnostic nodes, and failure outcomes through causal relations.

Shu-Xun Yang, Yi-Dong Wang, Zhuo-Er Feng et al. · 0 citations

#natural language process... Preprint Sep 2026

MTAC-IFBench: Benchmarking Instruction-Following in Multi-Turn Agentic Coding

Recently, the rapid development of large language models (LLMs) has reshaped software engineering by enabling autonomous code agents that plan, execute, and utilize external tools iteratively to tackle complex tasks. Beyond achieving functional correctness, these agents must faithfully follow process instructions and c...

Bo-Si Wen, Cun-Xiang Wang, Jia-Yi Gui et al. · 0 citations