16 citations · 19 across the 10 of their papers we have counts for
13 papers
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…
Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR Decomposition
Nishant Yadav, Nicholas Monath, Manzil Zaheer +1
Cross-encoder models, which jointly encode and score a query-item pair, are prohibitively expensive for direct k-nearest neighbor (k-NN) search. Consequently, k-NN search typically…
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining
Nicholas Monath, Manzil Zaheer, Kelsey Allen +1
Dual encoder models are ubiquitous in modern classification and retrieval. Crucial for training such dual encoders is an accurate estimation of gradients from the partition functio…
Autoregressive Structured Prediction with Language Models
Tianyu Liu, Yuchen Jiang, Nicholas Monath +2
Recent years have seen a paradigm shift in NLP towards using pretrained language models ({PLM}) for a wide range of tasks. However, there are many difficult design decisions to rep…
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization
Nishant Yadav, Nicholas Monath, Rico Angell +2
Efficient k-nearest neighbor search is a fundamental task, foundational for many problems in NLP. When the similarity is measured by dot-product between dual-encoder vectors or $\e…
Longtonotes: OntoNotes with Longer Coreference Chains
Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru +4
Ontonotes has served as the most important benchmark for coreference resolution. However, for ease of annotation, several long documents in Ontonotes were split into smaller parts.…
Unsupervised Opinion Summarization Using Approximate Geodesics
Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey +2
Opinion summarization is the task of creating summaries capturing popular opinions from user reviews. In this paper, we introduce Geodesic Summarizer (GeoSumm), a novel system to p…
Sublinear Time Approximation of Text Similarity Matrices
Archan Ray, Nicholas Monath, Andrew McCallum +1
We study algorithms for approximating pairwise similarity matrices that arise in natural language processing. Generally, computing a similarity matrix for data points requires…
Entity Linking and Discovery via Arborescence-based Supervised Clustering
Dhruv Agarwal, Rico Angell, Nicholas Monath +1
Previous work has shown promising results in performing entity linking by measuring not only the affinities between mentions and entities but also those amongst mentions. In this p…