Differentially private stochastic gradient descent (DP-SGD) adds noise t...
We introduce MAmmoTH, a series of open-source large language models (LLM...
Large Language Models (LLMs) are becoming increasingly smart and autonom...
We introduce TacoBot, a user-centered task-oriented digital assistant
de...
As opposed to general English, many concepts in biomedical terminology h...
Text-guided image editing is widely needed in daily life, ranging from
p...
We introduce Mind2Web, the first dataset for developing and evaluating
g...
This paper studies a new task of federated learning (FL) for semantic
pa...
Conventional supervised approaches for text-to-SQL parsing often require...
We explore testing the reasoning ability of large language models (LLMs)...
Despite recent progress in text-to-SQL parsing, current semantic parsers...
A recent focus of large language model (LLM) development, as exemplified...
Prompt tuning, in which a base pretrained model is adapted to each task ...
Privacy concerns have attracted increasing attention in data-driven prod...
We present TacoBot, a task-oriented dialogue system built for the inaugu...
Retrosynthesis is a procedure where a molecule is transformed into poten...
To reap the promised gain achieved by distributed reconfigurable intelli...
Synthesizing QA pairs with a question generator (QG) on the target domai...
The strong few-shot in-context learning capability of large pre-trained
...
While Pre-trained Language Models (PLMs) internalize a great amount of w...
Long story generation (LSG) is one of the coveted goals in natural langu...
Existing studies on semantic parsing focus primarily on mapping a
natura...
We present ReasonBert, a pre-training method that augments language mode...
This letter investigates a wireless communication system deploying
distr...
Texts convey sophisticated knowledge. However, texts also convey sensiti...
While most neural generative models generate outputs in a single pass, t...
Clinical question answering (QA) aims to automatically answer questions ...
We present a large challenging dataset, COUGH, for COVID-19 FAQ retrieva...
Learning to capture text-table alignment is essential for table related ...
Intelligent reflect surface (IRS) is a potential technology to build
pro...
Code retrieval is a key task aiming to match natural and programming
lan...
State-of-the-art question answering (QA) relies upon large amounts of
tr...
In this letter, we optimize the channel estimator of the cascaded channe...
In this paper, we investigate an intelligent reflect surface (IRS) assis...
Relational tables on the Web store a vast amount of knowledge. Owing to ...
Nowadays, the interpretability of machine learning models is becoming
in...
Despite the widely successful applications, bootstrapping and fine-tunin...
Machine reading comprehension has made great progress in recent years ow...
Annotating datasets for question answering (QA) tasks is very costly, as...
This paper makes one of the first efforts toward automatically generatin...
Routing newly posted questions (a.k.a cold questions) to potential answe...
As a promising paradigm, interactive semantic parsing has shown to impro...
Table is a popular data format to organize and present relational
inform...
Distant supervision (DS) has been widely used to automatically construct...
This paper investigates a new task named Conversational Question Generat...
Unstructured clinical texts contain rich health-related information. To
...
Motivation: Graph embedding learning which aims to automatically learn
l...
To accelerate software development, much research has been performed to ...
Given a text description, most existing semantic parsers synthesize a pr...
Stack Overflow (SO) has been a great source of natural language question...