Mingxuan Yuan

We propose a projection-based scoring function in KV cache eviction for LLM acceleration.

Based on systematic empirical analysis on post-training compression, we propose a calibration data curation framework to help pruning and quantization methods better preserve critical LLM capabilities.

We propose GRiD, a framework that grounds reasoning in knowledge-enhanced dependency graph, ensures logical consistency, and improves reasoning accuracy across various benchmarks.