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7 accepted papers

2026

FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning

ICLR 2026poster

Group relative policy optimization (GRPO) has demonstrated significant potential in improving the reasoning capabilities of large language models (LLMs) via reinforcement learning. However, its practical deployment is impeded by an excessively slow training process, primarily attributed to the compu…

Cited by 0SourcecodeScholar
2025

Formal Synthesis of Safe Kolmogorov-Arnold Network Controllers with Barrier Certificates

IJCAI 2025

Control barrier certificate generation is an efficient and powerful technique for the safe control of cyber-physical systems. Feed-forward neural networks (FNNs) are commonly used to synthesize control barrier certificates and safe controllers, but they struggle to effectively address the challenges

Cited by 0SourcePDFScholar
2021

Stable and Effective One-Step Method for Person Search

ICASSP 2021accepted

Person search, which requires both pedestrian detection and person re-identification, is a challenging computer vision task applied to real-world scenarios. The challenges faced by detection and re-identification, such as occlusion, poor illumination, confusing background, are still urgent for perso…

Cited by 0SourceScholar
2020

Multi-Task Learning in Autonomous Driving Scenarios Via Adaptive Feature Refinement Networks

ICASSP 2020accepted

Many deep learning applications benefit from multi-task learning with several related objectives. In autonomous driving scenarios, being able to accurately infer motion and spatial information is essential for scene understanding. In this paper, we combine an adaptive feature refinement module and a…

Cited by 0SourceScholar
2019

Ad-net: Attention Guided Network for Optical Flow Estimation Using Dilated Convolution

ICASSP 2019accepted

Variational models for optical flow estimation usually define an energy function that contains prior assumptions to explore rudimentary statistics of images. However, such methods cannot learn motion knowledge from the pre-prepared data and have many parameters that need to be set manually. Nowadays…

Cited by 0SourceScholar