activity
20232026
most citedPhoenix: Democratizing ChatGPT across Languages

20 citations · 52 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI2026

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

Jiaqi Liu, Shi Qiu, Mairui Li +33

Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail…

cs.CV2025

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models

Liqiang Jing, Guiming Hardy Chen, Ehsan Aghazadeh +2

Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities in multimodal tasks, but visual object hallucination remains a persistent issue. It refers to scenarios whe…

cs.CL2025

SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Hardy Chen, Haoqin Tu, Fali Wang +5

This work revisits the dominant supervised fine-tuning (SFT) then reinforcement learning (RL) paradigm for training Large Vision-Language Models (LVLMs), and reveals a key finding:…

cs.CV2024★ 8 cited

HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale

Junying Chen, Chi Gui, Ruyi Ouyang +10

The rapid development of multimodal large language models (MLLMs), such as GPT-4V, has led to significant advancements. However, these models still face challenges in medical multi…

cs.CL2024★ 1 cited

MileBench: Benchmarking MLLMs in Long Context

Dingjie Song, Shunian Chen, Guiming Hardy Chen +3

Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image task…

cs.CL2024★ 4 cited

ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Guiming Hardy Chen, Shunian Chen, Ruifei Zhang +7

Large vision-language models (LVLMs) have shown premise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they require…

cs.CL2024★ 9 cited

Humans or LLMs as the Judge? A Study on Judgement Biases

Guiming Hardy Chen, Shunian Chen, Ziche Liu +2

Adopting human and large language models (LLM) as judges (a.k.a human- and LLM-as-a-judge) for evaluating the performance of LLMs has recently gained attention. Nonetheless, this a…

cs.CL2023★ 3 cited

MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria

Wentao Ge, Shunian Chen, Guiming Hardy Chen +14

Multimodal large language models (MLLMs) have broadened the scope of AI applications. Existing automatic evaluation methodologies for MLLMs are mainly limited in evaluating queries…

cs.CL2023★ 3 cited

More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering

Bingsheng Yao, Guiming Chen, Ruishi Zou +7

While most existing works on LLM prompting techniques focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can…

cs.CL2023★ 4 cited

CMB: A Comprehensive Medical Benchmark in Chinese

Xidong Wang, Guiming Hardy Chen, Dingjie Song +8

Large Language Models (LLMs) provide a possibility to make a great breakthrough in medicine. The establishment of a standardized medical benchmark becomes a fundamental cornerstone…

cs.CL2023★ 20 cited

Phoenix: Democratizing ChatGPT across Languages

Zhihong Chen, Feng Jiang, Junying Chen +11

This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and…