56 citations · 99 across the 12 of their papers we have counts for
12 papers
DISCO: DISCovering Overfittings as Causal Rules for Text Classification Models
Zijian Zhang, Vinay Setty, Yumeng Wang +1
With the rapid advancement of neural language models, the deployment of over-parameterized models has surged, increasing the need for interpretable explanations comprehensible to h…
QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims
Venktesh V, Abhijit Anand, Avishek Anand +1
Automated fact checking has gained immense interest to tackle the growing misinformation in the digital era. Existing systems primarily focus on synthetic claims on Wikipedia, and…
The Surprising Effectiveness of Rankers Trained on Expanded Queries
Abhijit Anand, Venktesh V, Vinay Setty +1
An important problem in text-ranking systems is handling the hard queries that form the tail end of the query distribution. The difficulty may arise due to the presence of uncommon…
Context Aware Query Rewriting for Text Rankers using LLM
Abhijit Anand, Venktesh V, Vinay Setty +1
Query rewriting refers to an established family of approaches that are applied to underspecified and ambiguous queries to overcome the vocabulary mismatch problem in document ranki…
Query Understanding in the Age of Large Language Models
Avishek Anand, Venktesh V, Abhijit Anand +1
Querying, conversing, and controlling search and information-seeking interfaces using natural language are fast becoming ubiquitous with the rise and adoption of large-language mod…
Extreme Classification for Answer Type Prediction in Question Answering
Vinay Setty
Semantic answer type prediction (SMART) is known to be a useful step towards effective question answering (QA) systems. The SMART task involves predicting the top- knowledge gra…