94 citations · 253 across the 41 of their papers we have counts for
4 papers · 1 filter
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…
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels
Jasper Xian, Saron Samuel, Faraz Khoubsirat +7
We develop a method for training small-scale (under 100M parameter) neural information retrieval models with as few as 10 gold relevance labels. The method depends on generating sy…
CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems
Sara Rosenthal, Avirup Sil, Radu Florian +1
Retrieval Augmented Generation (RAG) has become a popular application for large language models. It is preferable that successful RAG systems provide accurate answers that are supp…
An Empirical Investigation into the Effect of Parameter Choices in Knowledge Distillation
Md Arafat Sultan, Aashka Trivedi, Parul Awasthy +1
We present a large-scale empirical study of how choices of configuration parameters affect performance in knowledge distillation (KD). An example of such a KD parameter is the meas…