Search Results for author:
Found 15 papers, 6 papers with code
In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval
We present an efficient training approach to text retrieval with dense representations that applies knowledge distillation using the ColBERT late-interaction ranking model.
Resources for Brewing BEIR: Reproducible Reference Models and an Official Leaderboard
BEIR is a benchmark dataset for zero-shot evaluation of information retrieval models across 18 different domain/task combinations.
AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation
This paper presents the AToMiC (Authoring Tools for Multimedia Content) dataset, designed to advance research in image/text cross-modal retrieval.
Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval
The advent of multilingual language models has generated a resurgence of interest in cross-lingual information retrieval (CLIR), which is the task of searching documents in one language with queries from another.
Evaluating Token-Level and Passage-Level Dense Retrieval Models for Math Information Retrieval
With the recent success of dense retrieval methods based on bi-encoders, studies have applied this approach to various interesting downstream retrieval tasks with good efficiency and in-domain effectiveness.
Ranked #1 on
Math Information Retrieval
on ARQMath
(using extra training data)
Sparsifying Sparse Representations for Passage Retrieval by Top-$k$ Masking
Sparse lexical representation learning has demonstrated much progress in improving passage retrieval effectiveness in recent models such as DeepImpact, uniCOIL, and SPLADE.
Text-to-Text Multi-view Learning for Passage Re-ranking
Recently, much progress in natural language processing has been driven by deep contextualized representations pretrained on large corpora.
Contextualized Query Embeddings for Conversational Search
This paper describes a compact and effective model for low-latency passage retrieval in conversational search based on learned dense representations.
Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling
A vital step towards the widespread adoption of neural retrieval models is their resource efficiency throughout the training, indexing and query workflows.
Ranked #15 on
Zero-shot Text Search
on BEIR
Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations
Pyserini is an easy-to-use Python toolkit that supports replicable IR research by providing effective first-stage retrieval in a multi-stage ranking architecture.
Cultural Vocal Bursts Intensity Prediction
Information Retrieval
+1
Designing Templates for Eliciting Commonsense Knowledge from Pretrained Sequence-to-Sequence Models
While internalized {``}implicit knowledge{''} in pretrained transformers has led to fruitful progress in many natural language understanding tasks, how to most effectively elicit such knowledge remains an open question.
Distilling Dense Representations for Ranking using Tightly-Coupled Teachers
We present an approach to ranking with dense representations that applies knowledge distillation to improve the recently proposed late-interaction ColBERT model.
Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting
Conversational search plays a vital role in conversational information seeking.
Conversational Question Reformulation via Sequence-to-Sequence Architectures and Pretrained Language Models
This paper presents an empirical study of conversational question reformulation (CQR) with sequence-to-sequence architectures and pretrained language models (PLMs).
TTTTTackling WinoGrande Schemas
We applied the T5 sequence-to-sequence model to tackle the AI2 WinoGrande Challenge by decomposing each example into two input text strings, each containing a hypothesis, and using the probabilities assigned to the "entailment" token as a score of the hypothesis.
Ranked #17 on
Coreference Resolution
on Winograd Schema Challenge
