9 citations · 30 across the 10 of their papers we have counts for
12 papers
Hierarchical Masked Diffusion Language Models
Parul Gupta, Satwik, Avni Aggarwal +5
Masked diffusion language models have emerged as an alternative to autoregressive models, enabling parallel token generation. However, standard masked diffusion language models use…
LLMs are Brittle to Simple Code Transformations: Introducing CETBench - A Benchmark for Code-Equivalence Checking
Neeva Oza, Ishaan Govil, Parul Gupta +3
We study how well LLMs can determine whether two programs are functionally equivalent. This is an important problem because benchmarking code equivalence helps assess LLM capabilit…
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants
G P Shrivatsa Bhargav, Sumit Neelam, Udit Sharma +10
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety o…
Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems
Aniruddha Deb, Neeva Oza, Sarthak Singla +3
While forward reasoning (i.e., find the answer given the question) has been explored extensively in recent literature, backward reasoning is relatively unexplored. We examine the b…
Image Manipulation via Multi-Hop Instructions -- A New Dataset and Weakly-Supervised Neuro-Symbolic Approach
Harman Singh, Poorva Garg, Mohit Gupta +7
We are interested in image manipulation via natural language text -- a task that is useful for multiple AI applications but requires complex reasoning over multi-modal spaces. We e…
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +22
Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…
Towards a Semantic Information Theory (Introducing Quantum Corollas)
Philip Tetlow, Dinesh Garg, Leigh Chase +4
The field of Information Theory is founded on Claude Shannon's seminal ideas relating to entropy. Nevertheless, his well-known avoidance of meaning (Shannon, 1948) still persists t…
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +21
Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…
Knowledge Graph Question Answering via SPARQL Silhouette Generation
Sukannya Purkayastha, Saswati Dana, Dinesh Garg +2
Knowledge Graph Question Answering (KGQA) has become a prominent area in natural language processing due to the emergence of large-scale Knowledge Graphs (KGs). Recently Neural Mac…
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27
Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…
The TechQA Dataset
Vittorio Castelli, Rishav Chakravarti, Saswati Dana +18
We introduce TechQA, a domain-adaptation question answering dataset for the technical support domain. The TechQA corpus highlights two real-world issues from the automated customer…
Span Selection Pre-training for Question Answering
Michael Glass, Alfio Gliozzo, Rishav Chakravarti +5
BERT (Bidirectional Encoder Representations from Transformers) and related pre-trained Transformers have provided large gains across many language understanding tasks, achieving a…