Chao Jiang

LLMs can now "think with visual latents" by generating masks directly from their internal representations, dramatically improving referring comprehension and segmentation.

CARNet achieves superior signal detection performance across diverse channel conditions by dynamically selecting specialized expert networks based on real-time channel estimates.

Training API-calling agents just got easier—synthetic data generation using LLMs eliminates the need for complex environments while boosting performance.

Treating negative samples differently based on their similarity to positives leads to a 13.1% boost in retrieval performance on complex queries.

By cleverly combining near-data processing with PCA-guided early exiting, NASZIP achieves a remarkable speedup in approximate nearest neighbor search, outperforming both CPU/GPU baselines and existing NDP accelerators.