Author

Monica S. Lam

3 papers indexed here

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#artificial intelligence Preprint Oct 2026

Did the Model Use That? Counterfactual Training Boosts Self-Attribution in Language Models

A fundamental challenge for explainable and accountable language models is revealing how external information influences their answers. This paper examines whether models are self-attributive: that is, whether they indicate when -- and only when -- their responses to questions are influenced by information provided alo...

Zing Z. X. Zhou, Jia-Cheng Sang, Yi-Lin Xu et al. · 0 citations

#artificial intelligence Preprint Apr 2026

SatIR: Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching

SatIR is proposed, a scalable, efficient, high-precision, high-recall, interpretable clinical trial retrieval method based on formal constraint satisfaction that consistently improves eligibility-aware retrieval over similarity-based baselines on the SIGIR 2016 dataset and a benchmark derived from TREC 2022.

Zikai Zhou, Yu-Fei Jin, Yi-Lin Xu et al. · 1 citation

#natural language process... Preprint Sep 2026

Accountable AI with Grounded, Faithful, Consistent, Actionable Rationales: A Case Study in Clinical Trial Matching with VERDICT

VERDICT is introduced, an LLM-based agent that translates a decision task, its constraints, and its policy into Satisfiability Modulo Theories (SMT), then derives the decision with SMT and MaxSMT solvers -- so policies are applied consistently and decisions are accountable by construction.

Zing Z. X. Zhou, Yu-Fei Jin, Yi-Lin Xu et al. · 0 citations