8 papers · 1 filter
ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models
Zhaoyan Jia, Chengwei Zhou, Gourav Datta +1
Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open challenge. Any-order generation…
Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision
Chengwei Zhou, Abu Masum, Xuming Chen +7
In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the logic chip integrated with a CMOS…
BRIDGE-EEG: Bridging Self-Supervised Pretraining and Efficient Deployment for Cross-Dataset EEG Classification
Meghna Roy Chowdhury, Chengwei Zhou, Haotian Yu +2
The growing use of electroencephalography (EEG) motivates automated analysis that is accurate, transferable, and deployable on constrained hardware. Recent EEG foundation models le…
PICasso: An AI-Enabled Design Framework for Autonomous Optimization of Silicon Photonic Devices
Deepak Vungarala, Deniz Najafi, Abdulrahman Aljoudi +6
We present PICasso, an AI-assisted framework for automated synthesis, verification, and optimization of photonic integrated circuits (PICs) from natural-language specifications. PI…
Sense Less, Infer More: Agentic Multimodal Transformers for Edge Medical Intelligence
Chengwei Zhou, Zhaoyan Jia, Haotian Yu +6
Edge-based multimodal medical monitoring requires models that balance diagnostic accuracy with severe energy constraints. Continuous acquisition of ECG, PPG, EMG, and IMU streams r…
Light-Bound Transformers: Hardware-Anchored Robustness for Silicon-Photonic Computer Vision Systems
Xuming Chen, Deniz Najafi, Chengwei Zhou +6
Deploying Vision Transformers (ViTs) on near-sensor analog accelerators demands training pipelines that are explicitly aligned with device-level noise and energy constraints. We in…
Toward Guarantees for Clinical Reasoning in Vision Language Models via Formal Verification
Vikash Singh, Debargha Ganguly, Haotian Yu +5
Vision-language models (VLMs) show promise in drafting radiology reports, yet they frequently suffer from logical inconsistencies, generating diagnostic impressions unsupported by…
RT-NeuS: Towards Real-Time Neuro-Symbolic Video Understanding via Adaptive Temporal Verification
Shawn Liang, Sahil Shah, Chengwei Zhou +5
Long-form video question answering (LVQA) requires answering natural-language queries about videos spanning minutes to hours, demanding temporal reasoning across thousands of frame…