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08/07/2023
AgentBench: Evaluating LLMs as Agents
Large Language Models (LLMs) are becoming increasingly smart and autonom...
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07/29/2023
Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System
We introduce TacoBot, a user-centered task-oriented digital assistant de...
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06/09/2023
Mind2Web: Towards a Generalist Agent for the Web
We introduce Mind2Web, the first dataset for developing and evaluating g...
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05/23/2023
Exploring Chain-of-Thought Style Prompting for Text-to-SQL
Conventional supervised approaches for text-to-SQL parsing often require...
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12/21/2022
What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis
Market sentiment analysis on social media content requires knowledge of ...
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12/19/2022
Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments
A key missing ability of current language models (LMs) is grounding to r...
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07/11/2022
Bootstrapping a User-Centered Task-Oriented Dialogue System
We present TacoBot, a task-oriented dialogue system built for the inaugu...
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03/16/2022
Reducing Flipping Errors in Deep Neural Networks
Deep neural networks (DNNs) have been widely applied in various domains ...
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03/16/2022
Shepherd Pre-trained Language Models to Develop a Train of Thought: An Iterative Prompting Approach
While Pre-trained Language Models (PLMs) internalize a great amount of w...
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09/10/2021
ReasonBERT: Pre-trained to Reason with Distant Supervision
We present ReasonBert, a pre-training method that augments language mode...
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05/16/2021
Graph-Free Knowledge Distillation for Graph Neural Networks
Knowledge distillation (KD) transfers knowledge from a teacher network t...
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12/24/2020
Learning with Retrospection
Deep neural networks have been successfully deployed in various domains ...
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11/01/2020
An Embarrassingly Simple Approach to Training Ternary Weight Networks
Deep neural networks (DNNs) have achieved great successes in various dom...
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10/24/2020
Structure-Grounded Pretraining for Text-to-SQL
Learning to capture text-table alignment is essential for table related ...
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10/09/2020
Local Region Knowledge Distillation
Knowledge distillation (KD) is an effective technique to transfer knowle...
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09/17/2020
Deep Collective Learning: Learning Optimal Inputs and Weights Jointly in Deep Neural Networks
It is well observed that in deep learning and computer vision literature...
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06/26/2020
TURL: Table Understanding through Representation Learning
Relational tables on the Web store a vast amount of knowledge. Owing to ...
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02/27/2020
Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?
Substantial efforts have been made on improving the generalization abili...
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12/05/2019
Easy-to-Hard: Leveraging Simple Questions for Complex Question Generation
This paper makes one of the first efforts toward automatically generatin...
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09/20/2019
Automatic Table completion using Knowledge Base
Table is a popular data format to organize and present relational inform...
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09/13/2019