3 papers
cs.CV2025
Self-Aug: Query and Entropy Adaptive Decoding for Large Vision-Language Models
Eun Woo Im, Muhammad Kashif Ali, Vivek Gupta
Large Vision-Language Models (LVLMs) have demonstrated remarkable multimodal capabilities, but they inherit the tendency to hallucinate from their underlying language models. While…
cs.LG2025
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
Anurag Garg, Muhammad Ali, Noah Hollmann +3
Foundation models for tabular data, like TabPFN, achieve strong performance on small datasets when pre-trained solely on synthetic data. We show that this performance can be signif…
cs.CL2024
Understanding the Interplay of Scale, Data, and Bias in Language Models: A Case Study with BERT
Muhammad Ali, Swetasudha Panda, Qinlan Shen +2
In the current landscape of language model research, larger models, larger datasets and more compute seems to be the only way to advance towards intelligence. While there have been…