We present Belebele, a multiple-choice machine reading comprehension (MR...
In this work, we develop and release Llama 2, a collection of pretrained...
Prompt tuning is one of the successful approaches for parameter-efficien...
Whether by processing videos with fixed resolution from start to end or
...
We introduce Progressive Prompts - a simple and efficient approach for
c...
Large multilingual language models typically rely on a single vocabulary...
Masked Language Modeling (MLM) has proven to be an essential component o...
Evaluating an explanation's faithfulness is desired for many reasons suc...
Using natural language as a supervision for training visual recognition
...
When a neural language model (LM) is adapted to perform a new task, what...
Distilling state-of-the-art transformer models into lightweight student
...
Conventional fine-tuning of pre-trained language models tunes all model
...
Large pre-trained language models (LMs) have demonstrated remarkable abi...
Current NLP models are predominantly trained through a pretrain-then-fin...
In this paper, we introduce UnifiedM2, a general-purpose misinformation ...
Few-shot learning has drawn researchers' attention to overcome the probl...
Closed-book question-answering (QA) is a challenging task that requires ...
Pre-trained language models have proven their unique powers in capturing...
Pretraining NLP models with variants of Masked Language Model (MLM)
obje...
Large transformer models have shown extraordinary success in achieving
s...
Recent work has suggested that language models (LMs) store both common-s...
We introduce the Scratchpad Mechanism, a novel addition to the
sequence-...
Community-based question answering (CQA) websites represent an important...
Emails in the workplace are often intentional calls to action for its
re...