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Yusen Hou

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ABLE: Representing and Mapping LLMs via Attribution-Based Large-model Embedding

ABLE (Attribution-Based Large-model Embedding), a framework that leverages the interpretability space to construct model representations by aggregating gradient-based feature attributions via a tokenizer-agnostic word-level alignment, captures model-specific input-sensitivity patterns rather than only surface-level outputs.

Zirui Wang, Yusen Hou, Shaofeng Liang et al. · 0 citations
Preprint Aug 2026

GenomeHarness: Harnessing Al Agents for Reliable Adaptation of Genome Language Models

GenomeHarness, an agentic harness for adapting genome language models through controlled search over fine-tuning recipes, improves mean test MCC in 47 settings, and shows gains on Genomic Benchmarks and on tasks where the root recipe is unstable or poorly matched.

Weicai Long, Yusen Hou, Houcheng Su et al. · 0 citations

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