8 papers
Test-Time Scaling via Error Localization
Rajiv Shailesh Chitale, Rahul Madhavan, Taneesh Gupta +2
Scaling inference-time computation has emerged as a reliable method to improve the performance of large language models on complex reasoning and programming tasks. However, standar…
Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG
Deep Ghosal, Ishani Sen, Wazib Ansar +1
Athlete assessment is a critical process for tracking physical progress and identifying elite talent. However, during mass recruitment drives, traditional methods rely on manual ob…
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…
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…
LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization
Koushik Viswanadha, Deepanway Ghosal, Somak Aditya
Logical reasoning is a key task for artificial intelligence due to it's role in major downstream tasks such as Question Answering, Summarization. Recent methods in improving the re…
The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzles
Vernon Y. H. Toh, Yew Ken Chia, Deepanway Ghosal +1
The releases of OpenAI's o-[n] series, such as o1, o3, and o4-mini, mark a significant paradigm shift in Large Language Models towards advanced reasoning capabilities. Notably, mod…