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Found 25 papers, 10 papers with code
NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders
Neural document rerankers are extremely effective in terms of accuracy.
Evaluating and Modeling Attribution for Cross-Lingual Question Answering
Based on these models, we improve the attribution level of a cross-lingual question-answering system.
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models
We take human annotations as a gold standard and show that a correlated automatic metric is suitable for development.
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network
We present an instance-based nearest neighbor approach to entity linking.
Decontextualization: Making Sentences Stand-Alone
Models for question answering, dialogue agents, and summarization often interpret the meaning of a sentence in a rich context and use that meaning in a new context.
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020.
Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking
In this work, we present an entity linking model which combines a Transformer architecture with large scale pretraining from Wikipedia links.
Ranked #10 on
Entity Linking
on AIDA-CoNLL
Entities as Experts: Sparse Memory Access with Entity Supervision
We introduce a new model - Entities as Experts (EAE) - that can access distinct memories of the entities mentioned in a piece of text.
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages
Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations.
Learning Cross-Context Entity Representations from Text
Language modeling tasks, in which words, or word-pieces, are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent representations of phrases.
Ranked #1 on
Entity Linking
on CoNLL-Aida
Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index
Existing open-domain question answering (QA) models are not suitable for real-time usage because they need to process several long documents on-demand for every input query.
Matching the Blanks: Distributional Similarity for Relation Learning
General purpose relation extractors, which can model arbitrary relations, are a core aspiration in information extraction.
Ranked #13 on
Relation Extraction
on SemEval-2010 Task 8
Natural Questions: a Benchmark for Question Answering Research
The public release consists of 307, 373 training examples with single annotations, 7, 830 examples with 5-way annotations for development data, and a further 7, 842 examples 5-way annotated sequestered as test data.
Ranked #7 on
Question Answering
on Natural Questions (long)
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
In this paper we study yes/no questions that are naturally occurring --- meaning that they are generated in unprompted and unconstrained settings.
Learning Entity Representations for Few-Shot Reconstruction of Wikipedia Categories
Language modeling tasks, in which words are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent representations of phrases.
Inherent Disagreements in Human Textual Inferences
We analyze human{'}s disagreements about the validity of natural language inferences.
Incremental Reading for Question Answering
Current state-of-the-art question answering models reason over an entire passage, not incrementally.
Phrase-Indexed Question Answering: A New Challenge for Scalable Document Comprehension
We formalize a new modular variant of current question answering tasks by enforcing complete independence of the document encoder from the question encoder.
Multi-Mention Learning for Reading Comprehension with Neural Cascades
Reading comprehension is a challenging task, especially when executed across longer or across multiple evidence documents, where the answer is likely to reoccur.
Learning Recurrent Span Representations for Extractive Question Answering
In this paper, we focus on this answer extraction task, presenting a novel model architecture that efficiently builds fixed length representations of all spans in the evidence document with a recurrent network.
Ranked #43 on
Question Answering
on SQuAD1.1 dev
Transforming Dependency Structures to Logical Forms for Semantic Parsing
In contrast{---}partly due to the lack of a strong type system{---}dependency structures are easy to annotate and have become a widely used form of syntactic analysis for many languages.
