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cs.CL2025

The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality

Aileen Cheng, Alon Jacovi, Amir Globerson +62

We introduce The FACTS Leaderboard, an online leaderboard suite and associated set of benchmarks that comprehensively evaluates the ability of language models to generate factually…

cs.CL2025

NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commonsense VQA Tasks

Aritra Dutta, Swapnanil Mukherjee, Deepanway Ghosal +1

Commonsense visual-question answering often hinges on knowledge that is missing from the image or the question. Small vision-language models (sVLMs) such as ViLT, VisualBERT and FL…

cs.CL2024

Not All Votes Count! Programs as Verifiers Improve Self-Consistency of Language Models for Math Reasoning

Vernon Y. H. Toh, Deepanway Ghosal, Soujanya Poria

Large language models (LLMs) have shown increasing competence in solving mathematical reasoning problems. However, many open-source LLMs still struggle with errors in calculation a…

cs.CL2024

Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided Interventions

Pengfei Hong, Navonil Majumder, Deepanway Ghosal +3

Recent advancements in Large Language Models (LLMs) have showcased striking results on existing logical reasoning benchmarks, with some models even surpassing human performance. Ho…

cs.CL2024

Improving Text-To-Audio Models with Synthetic Captions

Zhifeng Kong, Sang-gil Lee, Deepanway Ghosal +5

It is an open challenge to obtain high quality training data, especially captions, for text-to-audio models. Although prior methods have leveraged \textit{text-only language models…