activity
20212025
most citedOverview of the TREC 2022 deep learning track

15 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2025★ 15 cited

Overview of the TREC 2022 deep learning track

Nick Craswell, Bhaskar Mitra, Emine Yilmaz +4

This is the fourth year of the TREC Deep Learning track. As in previous years, we leverage the MS MARCO datasets that made hundreds of thousands of human annotated training labels…

cs.CL2023

Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues

Yue Feng, Yunlong Jiao, Animesh Prasad +3

User Satisfaction Modeling (USM) is one of the popular choices for task-oriented dialogue systems evaluation, where user satisfaction typically depends on whether the user's task g…

cs.CL2023★ 3 cited

Rethinking Semi-supervised Learning with Language Models

Zhengxiang Shi, Francesco Tonolini, Nikolaos Aletras +3

Semi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled data to improve model performance in downstream natural language processing (NLP) tasks…

cs.CL2022

MetaASSIST: Robust Dialogue State Tracking with Meta Learning

Fanghua Ye, Xi Wang, Jie Huang +3

Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general fr…

cs.LG2022

Just Mix Once: Worst-group Generalization by Group Interpolation

Giorgio Giannone, Serhii Havrylov, Jordan Massiah +2

Advances in deep learning theory have revealed how average generalization relies on superficial patterns in data. The consequences are brittle models with poor performance with shi…

cs.LG2022★ 2 cited

Integrated Weak Learning

Peter Hayes, Mingtian Zhang, Raza Habib +3

We introduce Integrated Weak Learning, a principled framework that integrates weak supervision into the training process of machine learning models. Our approach jointly trains the…

cs.HC2021

Proceedings of the CSCW 2021 Workshop -- Investigating and Mitigating Biases in Crowdsourced Data

Danula Hettiachchi, Mark Sanderson, Jorge Goncalves +5

This volume contains the position papers presented at CSCW 2021 Workshop - Investigating and Mitigating Biases in Crowdsourced Data, held online on 23rd October 2021, at the 24th A…