works on

From the 1 of 15 linked papers with an AI index.

collaborators

15 papers

cs.HC2026

VisionPulse: A Virtual Reality System Enabling Accessible Discovery and Navigation for Blind and Low Vision Users

Samuel Martin, Pooyan Fazli, Hasti Seifi

Free exploration is an important aspect of many engaging virtual reality (VR) experiences, yet remains largely inaccessible to blind and low vision (BLV) users due to its reliance…

cs.CV2026

CASHEW: Stabilizing Multimodal Reasoning via Iterative Trajectory Aggregation

Chaoyu Li, Fei Tao, Pooyan Fazli

The paper proposes CASHEW, an inference-time method that stabilizes multi-step reasoning in vision-language models by aggregating multiple reasoning trajectories with visual verifi…

cs.CV2026

EgoVITA: Learning to Plan and Verify for Egocentric Video Reasoning

Yogesh Kulkarni, Pooyan Fazli

Egocentric video understanding requires procedural reasoning under partial observability and continuously shifting viewpoints. Current multimodal large language models (MLLMs) stru…

cs.CV2026

FrameOracle: Learning What to See and How Much to See in Videos

Chaoyu Li, Tianzhi Li, Fei Tao +6

Vision-language models (VLMs) advance video understanding but operate under tight computational budgets, making performance dependent on selecting a small, high-quality subset of f…

cs.CV2026

ReGATE: Learning Faster and Better with Fewer Tokens in MLLMs

Chaoyu Li, Yogesh Kulkarni, Pooyan Fazli

The computational cost of training multimodal large language models (MLLMs) grows rapidly with the number of processed tokens. Existing efficiency methods mainly target inference v…

cs.CV2026

AVATAR: Reinforcement Learning to See, Hear, and Reason Over Video

Yogesh Kulkarni, Pooyan Fazli

Multimodal reasoning over long-horizon video is challenging due to the need for precise spatiotemporal fusion and alignment across modalities. While recent methods such as Group Re…