3 citations · 4 across the 11 of their papers we have counts for
12 papers
Hybrid-LUT: Channel-Aware Hybrid Lookup Table and Filtering for Efficient Image Denoising
Zhilin Ai, Boyu Li, Sidi Yang +5
Lookup table (LUT)-based image denoising methods have attracted increasing attention due to their high efficiency and hardware-friendly properties. However, existing RGB-LUT approa…
SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review
Ruoyu Wang, Jierun Chen, Shaowei Wang +7
Coding agents increasingly generate pull requests (PRs) for real-world software issues, yet one-shot PR generation remains open-loop: the PR is proposed without systematic review,…
What Makes Interaction Trajectories Effective for Training Terminal Agents?
Sidi Yang, Chaofan Tao, Jierun Chen +11
Stronger code agents are commonly assumed to be superior teachers for post-training, yet this assumption remains poorly disentangled from task difficulty, harness design, and stude…
CodeComp: Structural KV Cache Compression for Agentic Coding
Qiujiang Chen, Jing Xiong, Chenyang Zhao +2
Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value (KV) cache becomes the prim…
SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving
Chaofan Tao, Jierun Chen, Yuxin Jiang +11
We present SWE-Lego, a supervised fine-tuning (SFT) recipe designed to achieve state-ofthe-art performance in software engineering (SWE) issue resolving. In contrast to prevalent m…
From Denoising to Refining: A Corrective Framework for Vision-Language Diffusion Model
Yatai Ji, Teng Wang, Yuying Ge +4
Discrete diffusion models have emerged as a promising direction for vision-language tasks, offering bidirectional context modeling and theoretical parallelization. However, their p…
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables
Sidi Yang, Binxiao Huang, Yulun Zhang +3
While deep neural networks have revolutionized image denoising capabilities, their deployment on edge devices remains challenging due to substantial computational and memory requir…
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
Yatai Ji, Shilong Zhang, Jie Wu +6
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of…
Rolling Shutter Correction with Intermediate Distortion Flow Estimation
Mingdeng Cao, Sidi Yang, Yujiu Yang +1
This paper proposes to correct the rolling shutter (RS) distorted images by estimating the distortion flow from the global shutter (GS) to RS directly. Existing methods usually per…
Taming Lookup Tables for Efficient Image Retouching
Sidi Yang, Binxiao Huang, Mingdeng Cao +4
The widespread use of high-definition screens in edge devices, such as end-user cameras, smartphones, and televisions, is spurring a significant demand for image enhancement. Exist…
Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
Shanshan Lao, Yuan Gong, Shuwei Shi +5
Image quality assessment (IQA) algorithm aims to quantify the human perception of image quality. Unfortunately, there is a performance drop when assessing the distortion images gen…
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
Sidi Yang, Tianhe Wu, Shuwei Shi +5
No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual quality of images in accordance with human subjective perception. Unfortunately, existing NR-IQA method…