103 citations · 104 across the 15 of their papers we have counts for
15 papers
LEGO-RL: Harness-Native Reinforcement Learning for Coding Agents
Yiming Du, Yuxin Jiang, Tao Yuan +9
Reinforcement learning for coding agents increasingly relies on long-running agent harnesses to manage tool integration, repository contexts, and execution feedback. However, the n…
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…
GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning
Jingyi Wang, Lei Zhu, Tengjin Weng +8
Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Language Models (LLMs) by leveraging direct outcome verification instead of l…
FastCode: Fast and Cost-Efficient Code Understanding and Reasoning
Zhonghang Li, Zongwei Li, Yuxuan Chen +5
Repository-scale code reasoning is a cornerstone of modern AI-assisted software engineering, enabling Large Language Models (LLMs) to handle complex workflows from program comprehe…
From Verifiable Dot to Reward Chain: Harnessing Verifiable Reference-based Rewards for Reinforcement Learning of Open-ended Generation
Yuxin Jiang, Yufei Wang, Qiyuan Zhang +6
Reinforcement learning with verifiable rewards (RLVR) succeeds in reasoning tasks (e.g., math and code) by checking the final verifiable answer (i.e., a verifiable dot signal). How…
InSight-o3: Empowering Multimodal Foundation Models with Generalized Visual Search
Kaican Li, Lewei Yao, Jiannan Wu +7
The ability for AI agents to "think with images" requires a sophisticated blend of reasoning and perception. However, current open multimodal agents still largely fall short on the…
Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
Jiameng Huang, Baijiong Lin, Guhao Feng +3
Recent Large Reasoning Language Models (LRLMs) employ long chain-of-thought reasoning with complex reflection behaviors, typically signaled by specific trigger words (e.g., "Wait"…
The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs
Jierun Chen, Tiezheng Yu, Haoli Bai +11
Large vision-language models (VLMs) increasingly adopt post-training techniques such as long chain-of-thought (CoT) supervised fine-tuning (SFT) and reinforcement learning (RL) to…
Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models
Jierun Chen, Fangyun Wei, Jinjing Zhao +5
Referring expression comprehension (REC) involves localizing a target instance based on a textual description. Recent advancements in REC have been driven by large multimodal model…
StableKD: Breaking Inter-block Optimization Entanglement for Stable Knowledge Distillation
Shiu-hong Kao, Jierun Chen, S. H. Gary Chan
Knowledge distillation (KD) has been recognized as an effective tool to compress and accelerate models. However, current KD approaches generally suffer from an accuracy drop and/or…
Target-agnostic Source-free Domain Adaptation for Regression Tasks
Tianlang He, Zhiqiu Xia, Jierun Chen +2
Unsupervised domain adaptation (UDA) seeks to bridge the domain gap between the target and source using unlabeled target data. Source-free UDA removes the requirement for labeled s…
FIS-ONE: Floor Identification System with One Label for Crowdsourced RF Signals
Weipeng Zhuo, Ka Ho Chiu, Jierun Chen +4
Floor labels of crowdsourced RF signals are crucial for many smart-city applications, such as multi-floor indoor localization, geofencing, and robot surveillance. To build a predic…
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
Jierun Chen, Shiu-hong Kao, Hao He +4
To design fast neural networks, many works have been focusing on reducing the number of floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does no…
Semi-supervised Learning with Network Embedding on Ambient RF Signals for Geofencing Services
Weipeng Zhuo, Ka Ho Chiu, Jierun Chen +5
In applications such as elderly care, dementia anti-wandering and pandemic control, it is important to ensure that people are within a predefined area for their safety and well-bei…