Fang Liu

ContraFix is an agentic framework that improves automated vulnerability repair by using differential runtime evidence to pinpoint the root cause of bugs, achieving state-of-the-art performance on major benchmarks.

The paper introduces a novel paradigm where a fine-tuned LLM acts as an ancillary predictor to forecast likely advertisers, significantly improving ad recommendation systems by augmenting candidate generation and providing priors for downstream ranking.

The paper introduces NICE, a novel, theory-grounded diagnostic benchmark for assessing the social intelligence of LLMs, which reveals that current frontier models consistently struggle with specific facets of communication.