activity
20242026
most citedMACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

3 citations · 3 across the 14 of their papers we have counts for

collaborators

17 papers

cs.AI2026

2d-fet-bench: from spatial reasoning to fet design on flakes

Dunzhi Zhou, Chengyu Zhu, Gang Qiu +1

Field-effect transistor (FET) layouts on exfoliated two-dimensional flakes are typically drawn by hand for each flake, placing contacts and gates to match its position and outline…

cs.AI2026

Fork Where the Model Changes Its Mind: Belief-Shift Branching for Tree-Structured Reinforcement Learning

Bin Lei, Yu Li, Prafulla Kumar Choubey +7

Tree-structured rollouts give critic-free reinforcement learning with verifiable rewards (RLVR) step-level credit: fork a chain at an intermediate point, and sibling outcome differ…

cs.CE2026

FABRICA: Agentic CUDA-to-CSL Translation and Optimization for Wafer-Scale Systems

Yuebo Luo, Eliu Huerta, Venkatram Vishwanath +3

Porting GPU kernels across architectures requires architectural remapping, not syntax substitution. CUDA encodes decomposition, locality, and synchronization through threads, block…

cs.AR2026

HLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation

Yuebo Luo, Ahmad Sedigh Baroughi, Philip Stachura +4

Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them is costly, often requiring mon…

cs.AI2026

QFoldAgent: An Autonomous Quantum Optimization Multi-Agent System for Protein Structure Prediction

Winson Chen, Yuqi Zhang, Sixu Chen +3

Hybrid quantum-classical protein structure prediction depends strongly on Hamiltonian penalty weights, yet existing lattice-based workflows typically fix these coefficients by hand…

cs.LG2026

CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging

Shiyang Li, Haoyang Chen, Mattia Fazzini +1

Debugging CUDA programs has long been challenging because failures often arise from subtle interactions among hardware behavior, compiler decisions, memory hierarchy, and asynchron…

cs.AI2026

Stateful Reasoning via Insight Replay

Bin Lei, Caiwen Ding, Jiachen Yang +2

Chain-of-Thought (CoT) reasoning has become a foundation for eliciting multi-step reasoning in large language models, but recent studies show that its benefits do not scale monoton…

cs.LG2026

CUDAHercules: Benchmarking Hardware-Aware Expert-level CUDA Optimization for LLMs

Shiyang Li, Zijian Zhang, Guangyan Sun +5

Large language models show promise for automated CUDA programming, however even the strongest coding models (e.g., Claude-Opus-4.6) may still fall short of expert-level, architectu…

cs.MA2026

StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning

Shiyang Li, Zijian Zhang, Winson Chen +3

Modern machine learning (ML) workloads increasingly rely on GPUs, yet achieving high end-to-end performance remains challenging due to dependencies on both GPU kernel efficiency an…

cs.PL2025

Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation

Le Chen, Nuo Xu, Winson Chen +7

Large language models (LLMs) have shown remarkable capabilities in code translation, yet their performance deteriorates in low-resource programming domains such as Fortran and emer…

cs.CR2025

FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework

Nuo Xu, Zhaoting Gong, Ran Ran +3

Fully Homomorphic Encryption (FHE), particularly the CKKS scheme, is a promising enabler for privacy-preserving MLaaS, but its practical deployment faces a prohibitive barrier: it…

cs.CV2025

\textsc{GUI-Spotlight}: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding

Bin Lei, Nuo Xu, Ali Payani +4

Multimodal large language models (MLLMs) have markedly expanded the competence of graphical user-interface (GUI) systems, propelling them beyond controlled simulations into complex…

cs.AI2025

GuirlVG: Incentivize GUI Visual Grounding via Empirical Exploration on Reinforcement Learning

Weitai Kang, Bin Lei, Gaowen Liu +2

Graphical user interface visual grounding (GUI-VG), a core capability for GUI agents, has primarily relied on supervised fine-tuning (SFT) of multimodal large language models (MLLM…

cs.AI2025

InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction

Bin Lei, Weitai Kang, Zijian Zhang +8

This paper introduces \textsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, images, audio, and video. Unlik…

cs.LG2025

Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration

Le Chen, Bin Lei, Dunzhi Zhou +4

Translating legacy Fortran code into C++ is a crucial step in modernizing high-performance computing (HPC) applications. However, the scarcity of high-quality, parallel Fortran-to-…

eess.SY2025

Observer-Based Data-Driven Consensus Control for Nonlinear Multi-Agent Systems against DoS and FDI attacks

Yi Zhang, Bin Lei, Mohamadamin Rajabinezhad +2

Existing data-driven control methods generally do not address False Data Injection (FDI) and Denial-of-Service (DoS) attacks simultaneously. This letter introduces a distributed da…

cs.AI2024★ 3 cited

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

Bin Lei, Yi Zhang, Shan Zuo +2

Recent advancements in large language models, such as GPT-4, have demonstrated remarkable capabilities in processing standard queries. Despite these advancements, their performance…