research
∙
06/01/2023
Learning Transformer Programs
Recent research in mechanistic interpretability has attempted to reverse...
share
research
∙
05/27/2023
Fine-Tuning Language Models with Just Forward Passes
Fine-tuning language models (LMs) has yielded success on diverse downstr...
research
∙
05/24/2023
CSTS: Conditional Semantic Textual Similarity
Semantic textual similarity (STS) has been a cornerstone task in NLP tha...
research
∙
05/24/2023
Privacy Implications of Retrieval-Based Language Models
Retrieval-based language models (LMs) have demonstrated improved interpr...
research
∙
05/24/2023
Adapting Language Models to Compress Contexts
Transformer-based language models (LMs) are powerful and widely-applicab...
research
∙
05/24/2023
Enabling Large Language Models to Generate Text with Citations
Large language models (LLMs) have emerged as a widely-used tool for info...
research
∙
05/16/2023
What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning
Large language models (LLMs) exploit in-context learning (ICL) to solve ...
research
∙
12/20/2022
Controllable Text Generation with Language Constraints
We consider the task of text generation in language models with constrai...
research
∙
12/19/2022
Training Trajectories of Language Models Across Scales
Scaling up language models has led to unprecedented performance gains, b...
research
∙
10/26/2022
MABEL: Attenuating Gender Bias using Textual Entailment Data
Pre-trained language models encode undesirable social biases, which are ...
research
∙
10/26/2022
Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models
Masked language models like BERT can perform text classification in a ze...
research
∙
10/20/2022
Finding Dataset Shortcuts with Grammar Induction
Many NLP datasets have been found to contain shortcuts: simple decision ...
research
∙
10/11/2022
A Kernel-Based View of Language Model Fine-Tuning
It has become standard to solve NLP tasks by fine-tuning pre-trained lan...
research
∙
05/30/2022
Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models
Pre-trained masked language models successfully perform few-shot learnin...
research
∙
05/25/2022
Refining Query Representations for Dense Retrieval at Test Time
Dense retrieval uses a contrastive learning framework to learn dense rep...
research
∙
05/25/2022
Training Language Models with Memory Augmentation
Recent work has improved language models remarkably by equipping them wi...
research
∙
05/25/2022
Generating Natural Language Proofs with Verifier-Guided Search
Deductive reasoning (drawing conclusions from assumptions) is a challeng...
research
∙
05/17/2022
Recovering Private Text in Federated Learning of Language Models
Federated learning allows distributed users to collaboratively train a m...
research
∙
04/25/2022
Can Rationalization Improve Robustness?
A growing line of work has investigated the development of neural NLP mo...
research
∙
04/01/2022
Structured Pruning Learns Compact and Accurate Models
The growing size of neural language models has led to increased attentio...
research
∙
02/16/2022
Should You Mask 15
Masked language models conventionally use a masking rate of 15 belief th...
research
∙
12/16/2021
Ditch the Gold Standard: Re-evaluating Conversational Question Answering
Conversational question answering (CQA) systems aim to provide natural-l...
research
∙
09/28/2021
Single-dataset Experts for Multi-dataset Question Answering
Many datasets have been created for training reading comprehension model...
research
∙
09/17/2021
Simple Entity-Centric Questions Challenge Dense Retrievers
Open-domain question answering has exploded in popularity recently due t...
research
∙
09/16/2021
Phrase Retrieval Learns Passage Retrieval, Too
Dense retrieval methods have shown great promise over sparse retrieval m...
research
∙
04/26/2021
Non-Parametric Few-Shot Learning for Word Sense Disambiguation
Word sense disambiguation (WSD) is a long-standing problem in natural la...
research
∙
04/18/2021
SimCSE: Simple Contrastive Learning of Sentence Embeddings
This paper presents SimCSE, a simple contrastive learning framework that...
research
∙
04/12/2021
Factual Probing Is [MASK]: Learning vs. Learning to Recall
Petroni et al. (2019) demonstrated that it is possible to retrieve world...
research
∙
01/01/2021
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020. The competition...
research
∙
12/31/2020
Making Pre-trained Language Models Better Few-shot Learners
The recent GPT-3 model (Brown et al., 2020) achieves remarkable few-shot...
research
∙
12/23/2020
Learning Dense Representations of Phrases at Scale
Open-domain question answering can be reformulated as a phrase retrieval...
research
∙
10/24/2020
A Frustratingly Easy Approach for Joint Entity and Relation Extraction
End-to-end relation extraction aims to identify named entities and extra...
research
∙
10/12/2020
TextHide: Tackling Data Privacy in Language Understanding Tasks
An unsolved challenge in distributed or federated learning is to effecti...
research
∙
04/10/2020
Dense Passage Retrieval for Open-Domain Question Answering
Open-domain question answering relies on efficient passage retrieval to ...
research
∙
11/10/2019
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
This paper presents a general approach for open-domain question answerin...
research
∙
10/22/2019
MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension
We present the results of the Machine Reading for Question Answering (MR...
research
∙
09/11/2019
A Discrete Hard EM Approach for Weakly Supervised Question Answering
Many question answering (QA) tasks only provide weak supervision for how...
research
∙
07/26/2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Language model pretraining has led to significant performance gains but ...
research
∙
07/24/2019
SpanBERT: Improving Pre-training by Representing and Predicting Spans
We present SpanBERT, a pre-training method that is designed to better re...
research
∙
08/21/2018
CoQA: A Conversational Question Answering Challenge
Humans gather information by engaging in conversations involving a serie...
research
∙
03/31/2017
Reading Wikipedia to Answer Open-Domain Questions
This paper proposes to tackle open- domain question answering using Wiki...
research
∙
06/09/2016
A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
Enabling a computer to understand a document so that it can answer compr...
research
∙
01/16/2013
