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08/31/2023
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
We present Belebele, a multiple-choice machine reading comprehension (MR...
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07/18/2023
Llama 2: Open Foundation and Fine-Tuned Chat Models
In this work, we develop and release Llama 2, a collection of pretrained...
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05/06/2023
Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization
Prompt tuning is one of the successful approaches for parameter-efficien...
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04/01/2023
SVT: Supertoken Video Transformer for Efficient Video Understanding
Whether by processing videos with fixed resolution from start to end or ...
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01/29/2023
Progressive Prompts: Continual Learning for Language Models
We introduce Progressive Prompts - a simple and efficient approach for c...
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01/25/2023
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
Large multilingual language models typically rely on a single vocabulary...
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12/10/2022
Uniform Masking Prevails in Vision-Language Pretraining
Masked Language Modeling (MLM) has proven to be an essential component o...
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05/25/2022
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI
Evaluating an explanation's faithfulness is desired for many reasons suc...
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12/27/2021
A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision
Using natural language as a supervision for training visual recognition ...
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12/06/2021
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks
When a neural language model (LM) is adapted to perform a new task, what...
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10/16/2021
Sparse Distillation: Speeding Up Text Classification by Using Bigger Models
Distilling state-of-the-art transformer models into lightweight student ...
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10/14/2021
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning
Conventional fine-tuning of pre-trained language models tunes all model ...
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04/29/2021
Entailment as Few-Shot Learner
Large pre-trained language models (LMs) have demonstrated remarkable abi...
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04/18/2021
On the Influence of Masking Policies in Intermediate Pre-training
Current NLP models are predominantly trained through a pretrain-then-fin...
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04/12/2021
On Unifying Misinformation Detection
In this paper, we introduce UnifiedM2, a general-purpose misinformation ...
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03/17/2021
Towards Few-Shot Fact-Checking via Perplexity
Few-shot learning has drawn researchers' attention to overcome the probl...
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12/31/2020
Studying Strategically: Learning to Mask for Closed-book QA
Closed-book question-answering (QA) is a challenging task that requires ...
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12/31/2020
CLEAR: Contrastive Learning for Sentence Representation
Pre-trained language models have proven their unique powers in capturing...
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06/15/2020
To Pretrain or Not to Pretrain: Examining the Benefits of Pretraining on Resource Rich Tasks
Pretraining NLP models with variants of Masked Language Model (MLM) obje...
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06/08/2020
Linformer: Self-Attention with Linear Complexity
Large transformer models have shown extraordinary success in achieving s...
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06/07/2020
Language Models as Fact Checkers?
Recent work has suggested that language models (LMs) store both common-s...
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06/12/2019
Keeping Notes: Conditional Natural Language Generation with a Scratchpad Mechanism
We introduce the Scratchpad Mechanism, a novel addition to the sequence-...
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04/22/2018
Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching
Community-based question answering (CQA) websites represent an important...
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12/26/2017
