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20212025
most citedEvaluating Large Language Models Trained on Code

1.5k citations · 2.1k across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

VISTA: A Visual and Textual Attention Dataset for Interpreting Multimodal Models

Harshit, Tolga Tasdizen

The recent developments in deep learning led to the integration of natural language processing (NLP) with computer vision, resulting in powerful integrated Vision and Language Mode…

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★ 3 cited

Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance

Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3

The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…

cs.CL2024

Losing Visual Needles in Image Haystacks: Vision Language Models are Easily Distracted in Short and Long Contexts

Aditya Sharma, Michael Saxon, William Yang Wang

We present LoCoVQA, a dynamic benchmark generator for evaluating long-context extractive reasoning in vision language models (VLMs). LoCoVQA augments test examples for mathematical…

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…