1 citations · 1 across the 8 of their papers we have counts for
8 papers
The Percept-V Challenge: Can Multimodal LLMs Crack Simple Perception Problems?
Samrajnee Ghosh, Naman Agarwal, Ashish Goswami +4
Cognitive science research treats visual perception, the ability to understand and make sense of a visual input, as one of the early developmental signs of intelligence. Its TVPS-4…
SSP: Self-Supervised Prompting for Cross-Lingual Transfer to Low-Resource Languages using Large Language Models
Vipul Rathore, Aniruddha Deb, Ankish Chandresh +2
Recently, very large language models (LLMs) have shown exceptional performance on several English NLP tasks with just in-context learning (ICL), but their utility in other language…
RetinaQA: A Robust Knowledge Base Question Answering Model for both Answerable and Unanswerable Questions
Prayushi Faldu, Indrajit Bhattacharya, Mausam
An essential requirement for a real-world Knowledge Base Question Answering (KBQA) system is the ability to detect the answerability of questions when generating logical forms. How…
FCoReBench: Can Large Language Models Solve Challenging First-Order Combinatorial Reasoning Problems?
Chinmay Mittal, Krishna Kartik, Mausam +1
Can the large language models (LLMs) solve challenging first-order combinatorial reasoning problems such as graph coloring, knapsack, and cryptarithmetic? By first-order, we mean t…
Few-shot Transfer Learning for Knowledge Base Question Answering: Fusing Supervised Models with In-Context Learning
Mayur Patidar, Riya Sawhney, Avinash Singh +3
Existing Knowledge Base Question Answering (KBQA) architectures are hungry for annotated data, which make them costly and time-consuming to deploy. We introduce the problem of few-…
DynaSemble: Dynamic Ensembling of Textual and Structure-Based Models for Knowledge Graph Completion
Ananjan Nandi, Navdeep Kaur, Parag Singla +1
We consider two popular approaches to Knowledge Graph Completion (KGC): textual models that rely on textual entity descriptions, and structure-based models that exploit the connect…