Junhao Chen

PairCoder boosts artifact verifiability by up to 3.9 times compared to traditional single-pass inference, revealing the power of collaborative programming in AI-generated outputs.

OVOW achieves unprecedented accuracy and speed in reconstructing 4D scenes from a single video, making it a game-changer for physics simulation in AI.

Achieving a 22.3% word error rate with just 240 ms latency, LipsFlow redefines the capabilities of Visual Speech Recognition in challenging multi-speaker environments.

Gazer achieves semantic correction in autoregressive visual models without any training, leading to improved output quality and accuracy.

Limited human oversight can dramatically enhance the safety and stability of self-evolving agents, challenging the notion that autonomy must come without guidance.

One model to control them all: Qwen-VLA achieves impressive zero-shot generalization across diverse robotic tasks and embodiments by unifying vision-language-action modeling.

Forget vague goals – robots learn to *really* listen when you tell them *how* to do things, boosting real-world manipulation success by 25%.

Forget training-free pipelines: high-quality, feedforward 3D editing is now possible by learning directly from semantic-part transformations.