activity
20192025
most citedEvaluating Large Language Models Trained on Code

1.5k citations · 1.7k across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2025

ScheduleMe: Multi-Agent Calendar Assistant

Oshadha Wijerathne, Amandi Nimasha, Dushan Fernando +2

Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper pre…

cs.CL2025★ 5 cited

FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging

Zichen Tang, Haihong E, Ziyan Ma +10

We introduce FinanceReasoning, a novel benchmark designed to evaluate the reasoning capabilities of large reasoning models (LRMs) in financial numerical reasoning problems. Compare…

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

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…

cs.CL2023

GPT-4 Technical Report

OpenAI, Josh Achiam, Steven Adler +278

We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-wor…

cs.CL2021★ 33 cited

WebGPT: Browser-assisted question-answering with human feedback

Reiichiro Nakano, Jacob Hilton, Suchir Balaji +15

We fine-tune GPT-3 to answer long-form questions using a text-based web-browsing environment, which allows the model to search and navigate the web. By setting up the task so that…