Author

N. Singh

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Review Aug 2026

How Do Agents Fail on AutoResearch: End-to-End Diagnostic Evaluation on 100 Real-World Frontier Research Tasks

AutoResearchEval, featuring 100 tasks grounded in published frontier science across 7 scientific domains and the full research lifecycle, and ARFT, a framework of 45 empirically-grounded failure patterns to enable scalable fine-grained attribution, are introduced.

Yanlin Fei, Nazhou Liu, Xinmiao Yu et al. · 2 citations · ⚡1

#machine learning Preprint Sep 2026

Train What You Deploy: Closing the MLP Reachability Gap in Low-Rank Clone Distillation

This work shows that a state-of-the-art weight-inheritance distiller, Low-Rank Clone (LRC), deploys a full-width student MLP but ties training to a teacher-induced slice, leaving 62.5-81.4% of each deployed matrix's independent linear degrees of freedom unreachable-paid for at inference, never trainable.

Wen-Hui Chen, Zhi-Feng Li, Jie Zhou et al. · 0 citations

#artificial intelligence Review Aug 2026

Reconstruction: A Blind Benchmark for Recovering Research Ideas from Pre-Publication Bibliographies

Reconstruction is introduced, a blind idea-recovery benchmark that withholds the seed paper and all contemporaneous or future literature, and asks models to propose hypotheses that an independent large language model judge matches against the held-out ground-truth idea.

Shao-Long Chen, Yanlin Fei, Nazhou Liu et al. · 0 citations