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08/11/2023
Self-Alignment with Instruction Backtranslation
We present a scalable method to build a high quality instruction followi...
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05/23/2023
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
We introduce ZeroSCROLLS, a zero-shot benchmark for natural language und...
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05/18/2023
LIMA: Less Is More for Alignment
Large language models are trained in two stages: (1) unsupervised pretra...
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04/01/2023
Vision Transformers with Mixed-Resolution Tokenization
Vision Transformer models process input images by dividing them into a s...
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03/02/2023
X Fuse: Fusing Visual Information in Text-to-Image Generation
We introduce X Fuse, a general approach for conditioning on visual inf...
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01/10/2023
Scaling Laws for Generative Mixed-Modal Language Models
Generative language models define distributions over sequences of tokens...
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12/19/2022
Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor
Instruction tuning enables pretrained language models to perform new tas...
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12/17/2022
A Simple Baseline for Beam Search Reranking
Reranking methods in machine translation aim to close the gap between co...
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12/14/2022
Causes and Cures for Interference in Multilingual Translation
Multilingual machine translation models can benefit from synergy between...
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11/03/2022
LMentry: A Language Model Benchmark of Elementary Language Tasks
As the performance of large language models rapidly improves, benchmarks...
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05/22/2022
Instruction Induction: From Few Examples to Natural Language Task Descriptions
Large language models are able to perform a task by conditioning on a fe...
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04/10/2022
Breaking Character: Are Subwords Good Enough for MRLs After All?
Large pretrained language models (PLMs) typically tokenize the input str...
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03/30/2022
Transformer Language Models without Positional Encodings Still Learn Positional Information
Transformers typically require some form of positional encoding, such as...
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01/31/2022
Are Mutually Intelligible Languages Easier to Translate?
Two languages are considered mutually intelligible if their native speak...
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01/10/2022
SCROLLS: Standardized CompaRison Over Long Language Sequences
NLP benchmarks have largely focused on short texts, such as sentences an...
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12/14/2021
Learning to Retrieve Passages without Supervision
Dense retrievers for open-domain question answering (ODQA) have been sho...
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12/14/2021
Simple Local Attentions Remain Competitive for Long-Context Tasks
Many NLP tasks require processing long contexts beyond the length limit ...
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10/08/2021
A Few More Examples May Be Worth Billions of Parameters
We investigate the dynamics of increasing the number of model parameters...
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09/23/2021
ParaShoot: A Hebrew Question Answering Dataset
NLP research in Hebrew has largely focused on morphology and syntax, whe...
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08/25/2021
Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens
Standard pretrained language models operate on sequences of subword toke...
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08/12/2021
How Optimal is Greedy Decoding for Extractive Question Answering?
Fine-tuned language models use greedy decoding to answer reading compreh...
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07/20/2021
What Do You Get When You Cross Beam Search with Nucleus Sampling?
We combine beam search with the probabilistic pruning technique of nucle...
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04/19/2021
Can Latent Alignments Improve Autoregressive Machine Translation?
Latent alignment objectives such as CTC and AXE significantly improve no...
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04/15/2021
How to Train BERT with an Academic Budget
While large language models à la BERT are used ubiquitously in NLP, pret...
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03/01/2021
Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language
Current NLP datasets targeting ambiguity can be solved by a native speak...
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01/02/2021
Few-Shot Question Answering by Pretraining Span Selection
In a number of question answering (QA) benchmarks, pretrained models hav...
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01/02/2021
Coreference Resolution without Span Representations
Since the introduction of deep pretrained language models, most task-spe...
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12/29/2020
Transformer Feed-Forward Layers Are Key-Value Memories
Feed-forward layers constitute two-thirds of a transformer model's param...
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10/22/2020
The Turking Test: Can Language Models Understand Instructions?
Supervised machine learning provides the learner with a set of input-out...
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08/21/2020
Neural Machine Translation without Embeddings
Many NLP models follow the embed-contextualize-predict paradigm, in whic...
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04/03/2020
Aligned Cross Entropy for Non-Autoregressive Machine Translation
Non-autoregressive machine translation models significantly speed up dec...
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01/23/2020
Semi-Autoregressive Training Improves Mask-Predict Decoding
The recently proposed mask-predict decoding algorithm has narrowed the p...
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11/10/2019
Improving Transformer Models by Reordering their Sublayers
Multilayer transformer networks consist of interleaved self-attention an...
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11/07/2019
Blockwise Self-Attention for Long Document Understanding
We present BlockBERT, a lightweight and efficient BERT model that is des...
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11/01/2019
Generalization through Memorization: Nearest Neighbor Language Models
We introduce kNN-LMs, which extend a pre-trained neural language model (...
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10/29/2019
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
We present BART, a denoising autoencoder for pretraining sequence-to-seq...
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09/30/2019
Structural Language Models of Code
We address the problem of any-code completion - generating a missing pie...
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09/30/2019
Structural Language Models for Any-Code Generation
We address the problem of Any-Code Generation (AnyGen) - generating code...
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08/24/2019
BERT for Coreference Resolution: Baselines and Analysis
We apply BERT to coreference resolution, achieving strong improvements o...
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07/26/2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Language model pretraining has led to significant performance gains but ...
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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...
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06/11/2019
What Does BERT Look At? An Analysis of BERT's Attention
Large pre-trained neural networks such as BERT have had great recent suc...
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05/25/2019
Are Sixteen Heads Really Better than One?
Attention is a powerful and ubiquitous mechanism for allowing neural mod...
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05/02/2019
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
In the last year, new models and methods for pretraining and transfer le...
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04/19/2019
Constant-Time Machine Translation with Conditional Masked Language Models
Most machine translation systems generate text autoregressively, by sequ...
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02/05/2019
Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation
We consider the problem of making machine translation more robust to cha...
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10/20/2018
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference
Reasoning about implied relationships (e.g. paraphrastic, common sense, ...
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08/04/2018
code2seq: Generating Sequences from Structured Representations of Code
The ability to generate natural language sequences from source code snip...
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07/13/2018
Ultra-Fine Entity Typing
We introduce a new entity typing task: given a sentence with an entity m...
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05/29/2018
