565 citations · 711 across the 35 of their papers we have counts for
8 papers · 1 filter
PyTerrier-GenRank: The PyTerrier Plugin for Reranking with Large Language Models
Kaustubh D. Dhole
Using LLMs as rerankers requires experimenting with various hyperparameters, such as prompt formats, model choice, and reformulation strategies. We introduce PyTerrier-GenRank, a P…
ConQRet: Benchmarking Fine-Grained Evaluation of Retrieval Augmented Argumentation with LLM Judges
Kaustubh D. Dhole, Kai Shu, Eugene Agichtein
Computational argumentation, which involves generating answers or summaries for controversial topics like abortion bans and vaccination, has become increasingly important in today'…
Chatting with Logs: An exploratory study on Finetuning LLMs for LogQL
Vishwanath Seshagiri, Siddharth Balyan, Vaastav Anand +5
Logging is a critical function in modern distributed applications, but the lack of standardization in log query languages and formats creates significant challenges. Developers cur…
Generative Query Reformulation Using Ensemble Prompting, Document Fusion, and Relevance Feedback
Kaustubh D. Dhole, Ramraj Chandradevan, Eugene Agichtein
Query Reformulation (QR) is a set of techniques used to transform a user's original search query to a text that better aligns with the user's intent and improves their search exper…
GenQREnsemble: Zero-Shot LLM Ensemble Prompting for Generative Query Reformulation
Kaustubh Dhole, Eugene Agichtein
Query Reformulation(QR) is a set of techniques used to transform a user's original search query to a text that better aligns with the user's intent and improves their search experi…
DUQGen: Effective Unsupervised Domain Adaptation of Neural Rankers by Diversifying Synthetic Query Generation
Ramraj Chandradevan, Kaustubh D. Dhole, Eugene Agichtein
State-of-the-art neural rankers pre-trained on large task-specific training data such as MS-MARCO, have been shown to exhibit strong performance on various ranking tasks without do…
QueryExplorer: An Interactive Query Generation Assistant for Search and Exploration
Kaustubh D. Dhole, Shivam Bajaj, Ramraj Chandradevan +1
Formulating effective search queries remains a challenging task, particularly when users lack expertise in a specific domain or are not proficient in the language of the content. P…
KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants
Kaustubh D. Dhole
An effective multi-turn instruction-following assistant can be developed by creating a simulator that can generate useful interaction data. Apart from relying on its intrinsic weig…