most citedAnesSuite: A Comprehensive Benchmark and Dataset Suite for Anesthesiology Reasoning in LLMs

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Hallucination-aware Faithful Reasoning in Remote Sensing

Yi Liu, Jing Zhang, Xiang Feng +5

Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually unsupported reasoning that con…

cs.CL2026

DocScope: Benchmarking Verifiable Reasoning for Trustworthy Long-Document Understanding

Xiang Feng, Jiawei Zhou, Zhangfeng Huang +6

Evaluating whether Multimodal Large Language Models can produce trustworthy, verifiable reasoning over long, visually rich documents requires evaluation beyond end-to-end answer ac…

cs.CV2026

Omni-I2C: A Holistic Benchmark for High-Fidelity Image-to-Code Generation

Jiawei Zhou, Chi Zhang, Xiang Feng +6

We present Omni-I2C, a comprehensive benchmark designed to evaluate the capability of Large Multimodal Models (LMMs) in converting complex, structured digital graphics into executa…

cs.CL2025

REX-RAG: Reasoning Exploration with Policy Correction in Retrieval-Augmented Generation

Wentao Jiang, Xiang Feng, Zengmao Wang +5

Reinforcement learning (RL) is emerging as a powerful paradigm for enabling large language models (LLMs) to perform complex reasoning tasks. Recent advances indicate that integrati…

cs.CL2025★ 1 cited

AnesSuite: A Comprehensive Benchmark and Dataset Suite for Anesthesiology Reasoning in LLMs

Xiang Feng, Wentao Jiang, Zengmao Wang +5

The application of large language models (LLMs) in the medical field has garnered significant attention, yet their reasoning capabilities in more specialized domains like anesthesi…