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09/18/2023
Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adapter
Multilingual intelligent assistants, such as ChatGPT, have recently gain...
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09/07/2023
Large Language Models as Optimizers
Optimization is ubiquitous. While derivative-based algorithms have been ...
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05/30/2023
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
Large language models (LLMs) can learn to perform a wide range of natura...
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05/26/2023
Large Language Models as Tool Makers
Recent research shows the potential of enhancing the problem-solving abi...
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04/17/2023
Towards Robust Prompts on Vision-Language Models
With the advent of vision-language models (VLMs) that can perform in-con...
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03/01/2023
A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures
Despite huge gains in performance in natural language understanding via ...
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02/17/2023
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints
The limits of open-ended generative models are unclear, yet increasingly...
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11/21/2022
TEMPERA: Test-Time Prompting via Reinforcement Learning
Careful prompt design is critical to the use of large language models in...
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10/28/2022
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers
Large pre-trained language models have shown remarkable performance over...
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10/20/2022
Large Language Models Can Self-Improve
Large Language Models (LLMs) have achieved excellent performances in var...
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10/06/2022
Language Models are Multilingual Chain-of-Thought Reasoners
We evaluate the reasoning abilities of large language models in multilin...
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10/04/2022
Recitation-Augmented Language Models
We propose a new paradigm to help Large Language Models (LLMs) generate ...
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07/02/2022
Rationale-Augmented Ensembles in Language Models
Recent research has shown that rationales, or step-by-step chains of tho...
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05/21/2022
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
We propose a novel prompting strategy, least-to-most prompting, that ena...
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04/22/2022
Gravity aided navigation using Viterbi map matching algorithm
In GNSS-denied environments, aiding a vehicle's inertial navigation syst...
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04/05/2022
PaLM: Scaling Language Modeling with Pathways
Large language models have been shown to achieve remarkable performance ...
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03/31/2022
Probabilistic Map Matching for Robust Inertial Navigation Aiding
Robust aiding of inertial navigation systems in GNSS-denied environments...
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03/21/2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models
We explore a simple ensemble strategy, self-consistency, that significan...
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03/20/2022
Continual Sequence Generation with Adaptive Compositional Modules
Continual learning is essential for real-world deployment when there is ...
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01/28/2022
Chain of Thought Prompting Elicits Reasoning in Large Language Models
Although scaling up language model size has reliably improved performanc...
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12/15/2021
Measure and Improve Robustness in NLP Models: A Survey
As NLP models achieved state-of-the-art performances over benchmarks and...
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10/15/2021
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation
We investigate the robustness of vision transformers (ViTs) through the ...
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10/14/2021
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models
Recently, NLP models have achieved remarkable progress across a variety ...
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04/20/2021
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution
Single Image Super-resolution (SISR) produces high-resolution images wit...
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04/12/2021
Continual Learning for Text Classification with Information Disentanglement Based Regularization
Continual learning has become increasingly important as it enables NLP m...
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02/16/2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
Training and evaluation of fair classifiers is a challenging problem. Th...
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11/06/2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
ML models often exhibit unexpectedly poor behavior when they are deploye...
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10/12/2020
Measuring and Reducing Gendered Correlations in Pre-trained Models
Pre-trained models have revolutionized natural language understanding. H...
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10/05/2020
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation
NLP models are shown to suffer from robustness issues, i.e., a model's p...
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04/29/2020
ToTTo: A Controlled Table-To-Text Generation Dataset
We present ToTTo, an open-domain English table-to-text dataset with over...
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11/05/2019
Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems
Most literature in fairness has focused on improving fairness with respe...
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06/24/2019
Transfer of Machine Learning Fairness across Domains
If our models are used in new or unexpected cases, do we know if they wi...
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04/20/2018
Verifying Text Summaries of Relational Data Sets
We present a novel natural language query interface, the AggChecker, aim...
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11/25/2015
Maximum Likelihood Estimation for Single Linkage Hierarchical Clustering
We derive a statistical model for estimation of a dendrogram from single...
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11/24/2015
