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Home/Authors/Zhenting Qi

Zhenting Qi

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

NLP×2Architecture×1AI×1Vision×1

Frequent co-authors

Yilun Du2×
Chenyu Wang1×
Zishen Wan1×
Jeffrey Ma1×
Shvetank Prakash1×
Haebin Do1×

Research Timeline

2026
Dr. DocBench: A Comprehensive Benchmark for Expert-Level and Difficult Document Parsing

The paper introduces Dr. DocBench, a difficulty-aware, comprehensive benchmark designed to rigorously test expert-level and challenging document parsing capabilities for VLMs, demonstrating that current state-of-the-art models fail on complex, domain-specific structures.

On the Generalization Gap in Self-Evolving Language Model Reasoning

The paper investigates the limits of self-evolution in LLM reasoning under closed-loop settings, finding that while self-improvement is significant, it consistently falls short of perfect oracle supervision.

ArchEval: Measuring AI Agents as Computer Architects

This paper introduces ArchEval, a benchmark and platform for evaluating LLM agents on computer architecture design and optimization.

Highlighted terms show continued research focus across papers

Papers

cs.AREmpiricalRecentJul 3, 2026

ArchEval: Measuring AI Agents as Computer Architects

Chenyu Wang, Zishen Wan, Jeffrey Ma, Shvetank Prakash +7 more

This paper introduces ArchEval, a benchmark and platform for evaluating LLM agents on computer architecture design and optimization.

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cs.CLcs.AIcs.CVRecentMay 31, 2026

Dr. DocBench: A Comprehensive Benchmark for Expert-Level and Difficult Document Parsing

Minglai Yang, Xinyan Velocity Yu, Pengyuan Li, Xinyu Guo +21 more

The paper introduces Dr. DocBench, a difficulty-aware, comprehensive benchmark designed to rigorously test expert-level and challenging document parsing capabilities for VLMs, demonstrating that curre…

View →
cs.CLRecentMay 31, 2026

On the Generalization Gap in Self-Evolving Language Model Reasoning

Zhenting Qi, Susanna Maria Baby, Stefanie Anna Baby, Kan Yuan +4 more

The paper investigates the limits of self-evolution in LLM reasoning under closed-loop settings, finding that while self-improvement is significant, it consistently falls short of perfect oracle super…

View →