16 citations · 19 across the 10 of their papers we have counts for
5 papers · 1 filter
SIKeD: Self-guided Iterative Knowledge Distillation for mathematical reasoning
Shivam Adarsh, Kumar Shridhar, Caglar Gulcehre +2
Large Language Models (LLMs) can transfer their reasoning skills to smaller models by teaching them to generate the intermediate reasoning process required to solve multistep reaso…
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
Nicholas Monath, Will Grathwohl, Michael Boratko +3
In dense retrieval, deep encoders provide embeddings for both inputs and targets, and the softmax function is used to parameterize a distribution over a large number of candidate t…
Analysis of Plan-based Retrieval for Grounded Text Generation
Ameya Godbole, Nicholas Monath, Seungyeon Kim +3
In text generation, hallucinations refer to the generation of seemingly coherent text that contradicts established knowledge. One compelling hypothesis is that hallucinations occur…
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav, Nicholas Monath, Manzil Zaheer +2
Cross-encoder (CE) models which compute similarity by jointly encoding a query-item pair perform better than embedding-based models (dual-encoders) at estimating query-item relevan…
Incremental Extractive Opinion Summarization Using Cover Trees
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey +4
Extractive opinion summarization involves automatically producing a summary of text about an entity (e.g., a product's reviews) by extracting representative sentences that capture…