activity
20232025
most citedFinetuned Multimodal Language Models Are High-Quality Image-Text Data Filters

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…

cs.CL2025

Agent-Testing Agent: A Meta-Agent for Automated Testing and Evaluation of Conversational AI Agents

Sameer Komoravolu, Khalil Mrini

LLM agents are increasingly deployed to plan, retrieve, and write with tools, yet evaluation still leans on static benchmarks and small human studies. We present the Agent-Testing…

cs.CL2024★ 1 cited

Fast Prompt Alignment for Text-to-Image Generation

Khalil Mrini, Hanlin Lu, Linjie Yang +2

Text-to-image generation has advanced rapidly, yet aligning complex textual prompts with generated visuals remains challenging, especially with intricate object relationships and f…

cs.CV2024★ 1 cited

Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters

Weizhi Wang, Khalil Mrini, Linjie Yang +4

We propose a novel framework for filtering image-text data by leveraging fine-tuned Multimodal Language Models (MLMs). Our approach outperforms predominant filtering methods (e.g.,…

cs.CV2023★ 1 cited

InfiMM-Eval: Complex Open-Ended Reasoning Evaluation For Multi-Modal Large Language Models

Xiaotian Han, Quanzeng You, Yongfei Liu +9

Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence. These models not only excel in traditional vision-language tasks but a…