research
∙
05/23/2023
Difference-Masking: Choosing What to Mask in Continued Pretraining
Self-supervised learning (SSL) and the objective of masking-and-predicti...
share
research
∙
05/04/2023
Chain-of-Skills: A Configurable Model for Open-domain Question Answering
The retrieval model is an indispensable component for real-world knowled...
research
∙
04/26/2023
Using Implicit Feedback to Improve Question Generation
Question Generation (QG) is a task of Natural Language Processing (NLP) ...
research
∙
01/08/2023
InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers
We carried out a reproducibility study of InPars recipe for unsupervised...
research
∙
12/21/2022
Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation
Generalisation to unseen contexts remains a challenge for embodied navig...
research
∙
12/16/2022
Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving
The feasibility of collecting a large amount of expert demonstrations ha...
research
∙
10/22/2022
Open-domain Question Answering via Chain of Reasoning over Heterogeneous Knowledge
We propose a novel open-domain question answering (ODQA) framework for a...
research
∙
08/26/2022
Coalescing Global and Local Information for Procedural Text Understanding
Procedural text understanding is a challenging language reasoning task t...
research
∙
07/04/2022
Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding
We carry out a comprehensive evaluation of 13 recent models for ranking ...
research
∙
05/19/2022
Table Retrieval May Not Necessitate Table-specific Model Design
Tables are an important form of structured data for both human and machi...
research
∙
05/05/2022
Learn-to-Race Challenge 2022: Benchmarking Safe Learning and Cross-domain Generalisation in Autonomous Racing
We present the results of our autonomous racing virtual challenge, based...
research
∙
10/16/2021
Open Domain Question Answering over Virtual Documents: A Unified Approach for Data and Text
Due to its potential for a universal interface over both data and text, ...
research
∙
10/14/2021
Safety-aware Policy Optimisation for Autonomous Racing
To be viable for safety-critical applications, such as autonomous drivin...
research
∙
09/07/2021
Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models
Commonsense reasoning benchmarks have been largely solved by fine-tuning...
research
∙
12/19/2020
Lexically-constrained Text Generation through Commonsense Knowledge Extraction and Injection
Conditional text generation has been a challenging task that is yet to s...
research
∙
11/07/2020
Knowledge-driven Self-supervision for Zero-shot Commonsense Question Answering
Recent developments in pre-trained neural language modeling have led to ...
research
∙
10/28/2020
Flexible retrieval with NMSLIB and FlexNeuART
Our objective is to introduce to the NLP community an existing k-NN sear...
research
∙
10/30/2019
Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering
Non-extractive commonsense QA remains a challenging AI task, as it requi...
research
∙
10/08/2019
Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study
We focus on low-dimensional non-metric search, where tree-based approach...
research
∙
10/08/2019
Accurate and Fast Retrieval for Complex Non-metric Data via Neighborhood Graphs
We demonstrate that a graph-based search algorithm-relying on the constr...
research
∙
07/23/2019
Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations
This paper presents the submissions by Team Dr.Quad to the ACL-BioNLP 20...
research
∙
07/01/2019
Pentagon at MEDIQA 2019: Multi-task Learning for Filtering and Re-ranking Answers using Language Inference and Question Entailment
Parallel deep learning architectures like fine-tuned BERT and MT-DNN, ha...
research
∙
06/18/2018
Comparative Analysis of Neural QA models on SQuAD
The task of Question Answering has gained prominence in the past few dec...
research
∙
05/10/2018
Towards Inference-Oriented Reading Comprehension: ParallelQA
In this paper, we investigate the tendency of end-to-end neural Machine ...
research
∙
11/15/2017
CMU LiveMedQA at TREC 2017 LiveQA: A Consumer Health Question Answering System
In this paper, we present LiveMedQA, a question answering system that is...
research
∙
09/09/2017
Steering Output Style and Topic in Neural Response Generation
We propose simple and flexible training and decoding methods for influen...
research
∙
07/04/2017
CharManteau: Character Embedding Models For Portmanteau Creation
Portmanteaus are a word formation phenomenon where two words are combine...
research
∙
07/04/2017
Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Models
Variations in writing styles are commonly used to adapt the content to a...
research
∙
03/02/2017
