activity
20242026
most citedGPT-4o System Card

164 citations · 182 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Mimic Human Cognition, Master Multi-Image Reasoning: A Meta-Action Framework for Enhanced Visual Understanding

Jianghao Yin, Qingbin Li, Kun Sun +10

While Multimodal Large Language Models (MLLMs) excel at single-image understanding, they exhibit significantly degraded performance in multi-image reasoning scenarios. Multi-image…

cs.CL2026★ 18 cited

OpenAI GPT-5 System Card

Aaditya Singh, Adam Fry, Adam Perelman +483

This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…

cs.SE2025

A Systematic Study on Generating Web Vulnerability Proof-of-Concepts Using Large Language Models

Mengyao Zhao, Kaixuan Li, Lyuye Zhang +4

Recent advances in Large Language Models (LLMs) have brought remarkable progress in code understanding and reasoning, creating new opportunities and raising new concerns for softwa…

cs.CL2025

Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems

Shang-Chi Tsai, Yun-Nung Chen

With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…

cs.CV2025

3D Dynamics-Aware Manipulation: Endowing Manipulation Policies with 3D Foresight

Yuxin He, Ruihao Zhang, Xianzu Wu +3

The incorporation of world modeling into manipulation policy learning has pushed the boundary of manipulation performance. However, existing efforts simply model the 2D visual dyna…

cs.CL2024★ 164 cited

GPT-4o System Card

OpenAI, :, Aaron Hurst +416

GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's…

cs.CV2024

Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition

Cheng Liu, Xuyang Yan, Zekun Zhang +5

Action recognition has witnessed the development of a growing number of novel algorithms and datasets in the past decade. However, the majority of public benchmarks were constructe…