activity
20232026
most citedGPT-4o System Card

164 citations · 180 across the 19 of their papers we have counts for

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Showing cs.CLShow all

15 papers · 1 filter

cs.CL2026

PolyAlign: Conditional Human-Distribution Alignment

L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2

Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…

cs.CL2025

RTTC: Reward-Guided Collaborative Test-Time Compute

J. Pablo Muñoz, Jinjie Yuan

Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…

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.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.CL2025

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning

Erxin Yu, Jing Li, Ming Liao +7

Although large language models demonstrate strong performance across various domains, they still struggle with numerous bad cases in mathematical reasoning. Previous approaches to…

cs.CL2025★ 2 cited

SEA-LION: Southeast Asian Languages in One Network

Raymond Ng, Thanh Ngan Nguyen, Yuli Huang +28

Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority…

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.CL2024

CodeInsight: A Curated Dataset of Practical Coding Solutions from Stack Overflow

Nathanaël Beau, Benoît Crabbé

We introduce a novel dataset tailored for code generation, aimed at aiding developers in common tasks. Our dataset provides examples that include a clarified intent, code snippets…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024★ 1 cited

Beyond Performance: Quantifying and Mitigating Label Bias in LLMs

Yuval Reif, Roy Schwartz

Large language models (LLMs) have shown remarkable adaptability to diverse tasks, by leveraging context prompts containing instructions, or minimal input-output examples. However,…

cs.CL2024

Naive Bayes-based Context Extension for Large Language Models

Jianlin Su, Murtadha Ahmed, Wenbo +3

Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…

cs.CL2024

Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks

R. Patrick Xian, Alex J. Lee, Satvik Lolla +4

The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…

cs.CL2023

BLESS: Benchmarking Large Language Models on Sentence Simplification

Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez +4

We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how wel…

cs.CL2023★ 6 cited

Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

Xiuying Wei, Yunchen Zhang, Yuhang Li +4

Post-training quantization~(PTQ) of transformer language models faces significant challenges due to the existence of detrimental outliers in activations. We observe that these outl…

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…