news

Aug 20, 2026 All Leaks Count, Some Count More is accepted to the Findings of EMNLP 2026 (14.3% acceptance)! The paper measures how much of an LLM’s decision-driving reasoning is temporally contaminated (Shapley-DCLR) and blocks it at inference time without retraining (TimeSPEC).
Aug 03, 2026 The capstone of our backtesting line is live on arXiv: Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores proves the standard contamination check is uninformative and shows one defensible reference restores a leakage-adjusted score. In submission to TMLR, with code and data released.
May 25, 2026 Our new preprint on catching models that “peek” at the future is live on arXiv—with code to reproduce the claim-level leakage audit and TimeSPEC mitigation.
May 13, 2026 TEMPO is out: a training approach that teaches LLMs temporal discipline for trustworthy backtesting. Code released.
Jan 22, 2026 Thrilled that LAMP was selected as a Spotlight at AISTATS 2026—a lightweight way to audit whether a model’s explanations behave like they matter.