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Hongliang Li

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Preprint Aug 2026

ScienceFlow: A long-horizon agent for ML research, scientific discovery and beyond

Results on diverse long-horizon benchmarks demonstrate the efficacy of ScienceFlow's ability to sustain effective research processes, and demonstrates that efficient state management, adaptive exploration, and objective-aligned execution are critical for scaling autonomous research beyond short-horizon interactions.

Ming-Ming Zhao, Ji-Qian Dong, Kangping Xu et al. · 4 citations
#small language model Preprint Aug 2026

SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs

SHIFT-LLM, a training-free post-pruning correction framework that inserts a Linear Residual Adapter at each pruning site, consistently recovers accuracy lost to depth pruning across most configurations, achieving gains up to +15.7 points on Llama-3.1-8B-Instruct.

Ali Bahri, Hang Li, Hongliang Li et al. · 0 citations

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