2 citations · 3 across the 6 of their papers we have counts for
6 papers
Benchmarking Scientific Understanding and Reasoning for Video Generation using VideoScience-Bench
Lanxiang Hu, Abhilash Shankarampeta, Yixin Huang +7
The next frontier for video generation lies in developing models capable of zero-shot reasoning, where understanding real-world scientific laws is crucial for accurate physical out…
Evidence-Guided Schema Normalization for Temporal Tabular Reasoning
Ashish Thanga, Vibhu Dixit, Abhilash Shankarampeta +1
Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose an approach that recasts the task as automated knowledge base constructi…
Towards Interpretable and Inference-Optimal COT Reasoning with Sparse Autoencoder-Guided Generation
Daniel Zhao, Abhilash Shankarampeta, Lanxiang Hu +2
We propose a novel method that leverages sparse autoencoders (SAEs) and clustering techniques to analyze the internal token representations of large language models (LLMs) and guid…
TransientTables: Evaluating LLMs' Reasoning on Temporally Evolving Semi-structured Tables
Abhilash Shankarampeta, Harsh Mahajan, Tushar Kataria +2
Humans continuously make new discoveries, and understanding temporal sequence of events leading to these breakthroughs is essential for advancing science and society. This ability…
Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data
Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta +3
Numbers are crucial for various real-world domains such as finance, economics, and science. Thus, understanding and reasoning with numbers are essential skills for language models…
Enhancing Tabular Reasoning with Pattern Exploiting Training
Abhilash Reddy Shankarampeta, Vivek Gupta, Shuo Zhang
Recent methods based on pre-trained language models have exhibited superior performance over tabular tasks (e.g., tabular NLI), despite showing inherent problems such as not using…