Evaluation of Large Language Models (LLMs) is challenging because aligni...
Dense video captioning, a task of localizing meaningful moments and
gene...
In this work, we empirically show that updating pretrained LMs (350M, 1....
Training data attribution (TDA) techniques find influential training dat...
Generative retrieval has recently been gaining a lot of attention from t...
Large Language Models (LLMs) have demonstrated great capabilities in sol...
Large Language Models (LLMs) have shown enhanced capabilities of solving...
Open-domain conversation systems integrate multiple conversation skills ...
Aligning large language models (LLMs) to human values has become increas...
Instruction learning of Large Language Models (LLMs) has enabled zero-sh...
Recently, Language Models (LMs) instruction-tuned on multiple tasks, als...
We introduce REPLUG, a retrieval-augmented language modeling framework t...
Efficient video-language modeling should consider the computational cost...
Legal practitioners often face a vast amount of documents. Lawyers, for
...
Research on Korean grammatical error correction (GEC) is limited compare...
During zero-shot inference with language models (LMs), using hard prompt...
Meta-training, which fine-tunes the language model (LM) on various downs...
The text retrieval task is mainly performed in two ways: the bi-encoder
...
Pretrained Language Models (LMs) memorize a vast amount of knowledge dur...
Previous work has shown that there exists a scaling law between the size...
The recent advances of deep learning have dramatically changed how machi...
As the importance of identifying misinformation is increasing, many
rese...
Language Models (LMs) become outdated as the world changes; they often f...
Multi-hop retrieval is the task of retrieving a series of multiple docum...
Semi-structured query systems for document-oriented databases have many ...
Video-text retrieval has many real-world applications such as media
anal...
Large Language Models (LMs) are known to encode world knowledge in their...
A real-world information extraction (IE) system for semi-structured docu...
In open-domain question answering (QA), retrieve-and-read mechanism has ...
We review the EfficientQA competition from NeurIPS 2020. The competition...
The state of the art in open-domain question answering (QA) relies on an...
Deep learning approaches to semantic parsing require a large amount of
l...
Information Extraction (IE) for document images is often approached as a...
A sparse representation is known to be an effective means to encode prec...
We present the results of the Machine Reading for Question Answering (MR...
Generating diverse sequences is important in many NLP applications such ...
Existing open-domain question answering (QA) models are not suitable for...
WikiSQL is the task of mapping a natural language question to a SQL quer...
The current trend of extractive question answering (QA) heavily relies o...
Inspired by the principles of speed reading, we introduce Skim-RNN, a
re...
We show that relation extraction can be reduced to answering simple read...
We show that the task of question answering (QA) can significantly benef...
Machine comprehension (MC), answering a query about a given context
para...
In this paper, we study the problem of question answering when reasoning...
Diagrams are common tools for representing complex concepts, relationshi...