Publications
This is the full publication archive. For the broader research agenda and representative projects, visit the Research page.
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BELLA (Budget-Efficient LLM Selection via Automated skill-profiling), a framework that recommends optimal LLM selection for tasks through interpretable skill-based model selection.
A framework for semi-synthetic financial benchmark generation to enable rigorous and scalable evaluation of language models in finance.
A novel, high-difficulty benchmark designed to assess LM instruction-following capabilities for financial analysis tasks.
An exploration of language models for open-ended wargames, investigating AI systems’ ability to influence large-scale decisions with implications for safety and interpretability.
An investigation into whether language models can distinguish and estimate suspense in text sequences compared to human judgments.
A comprehensive evaluation framework for studying language models against reasoning-reinforced LMs across 20+ core NLP tasks in finance.
A cost-aware and uncertainty-based framework for dynamic 2D prediction in multi-stage classification systems.