6 papers
SweRank: Software Issue Localization with Code Ranking
Revanth Gangi Reddy, Tarun Suresh, JaeHyeok Doo +7
Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language issue description (e.g., bug report, f…
CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking
Tarun Suresh, Revanth Gangi Reddy, Yifei Xu +4
Effective code retrieval plays a crucial role in advancing code generation, bug fixing, and software maintenance, particularly as software systems increase in complexity. While cur…
Dialog Flow Induction for Constrainable LLM-Based Chatbots
Stuti Agrawal, Nishi Uppuluri, Pranav Pillai +5
LLM-driven dialog systems are used in a diverse set of applications, ranging from healthcare to customer service. However, given their generalization capability, it is difficult to…
FIRST: Faster Improved Listwise Reranking with Single Token Decoding
Revanth Gangi Reddy, JaeHyeok Doo, Yifei Xu +4
Large Language Models (LLMs) have significantly advanced the field of information retrieval, particularly for reranking. Listwise LLM rerankers have showcased superior performance…
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings
Revanth Gangi Reddy, Omar Attia, Yunyao Li +2
Ranking is a fundamental and popular problem in search. However, existing ranking algorithms usually restrict the granularity of ranking to full passages or require a specific dens…
Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization
Zixuan Zhang, Revanth Gangi Reddy, Kevin Small +2
Open-domain Question Answering (OpenQA) aims at answering factual questions with an external large-scale knowledge corpus. However, real-world knowledge is not static; it updates a…