291 citations · 957 across the 23 of their papers we have counts for
5 papers · 1 filter
NeuroLens: Learning Latent Embeddings of Neural Semantics from Chronic Recordings
Hanrui Lyu, Baiyuan Chen, Tianshu Tan +8
Understanding how neural activity represents higher-order cognition and how these representations evolve over time has long been a central pursuit in neuroscience. However, current…
Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores
Zeyu Zhang, Bradly C. Stadie
The standard check for contamination in LLM backtests is simple: compare scores before and after the training cutoff. We show this check is uninformative. Four flagship models fail…
TEMPO: Temporal Enforcement via Mode-Separated Policy Optimization for Trustworthy LLM Backtesting
Zeyu Zhang, Bradly C. Stadie
Backtesting large language models on historical events requires reasoning exclusively from information available before a specified cutoff date. Yet models routinely leak post-cuto…
Evolutionary System Prompt Learning for Reinforcement Learning in LLMs
Lunjun Zhang, Ryan Chen, Bradly C. Stadie
Building agentic systems that can autonomously self-improve from experience is a longstanding goal of AI. Large language models (LLMs) today primarily self-improve via two mechanis…
All Leaks Count, Some Count More: Interpretable Temporal Contamination Detection and Mitigation in LLM Backtesting
Zeyu Zhang, Ryan Chen, Bradly C. Stadie
Backtesting LLMs on resolved events assumes models reason only from pre-cutoff knowledge, yet pretrained models inevitably leak post-cutoff knowledge. We introduce a claim-level ev…