Lijun Wu

Unlock long-context reasoning in LLMs by turning agent trajectories into gold-standard QA pairs, outperforming models 8x larger on challenging reasoning tasks.

LLM datasets aren't independent islands: tracing their lineage reveals hidden redundancy, benchmark contamination, and opportunities for more diverse training data.

An 8B model can now generate scientific graphics code that rivals or surpasses the output of much larger proprietary models, thanks to a new dataset, benchmark, and reinforcement learning approach.