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08/30/2023
Quantifying Uncertainty in Answers from any Language Model via Intrinsic and Extrinsic Confidence Assessment
We introduce BSDetector, a method for detecting bad and speculative answ...
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08/23/2023
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning
In the realm of Large Language Models, the balance between instruction d...
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06/05/2023
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
Large language models (LLMs) are instruction followers, but it can be ch...
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04/06/2023
When do you need Chain-of-Thought Prompting for ChatGPT?
Chain-of-Thought (CoT) prompting can effectively elicit complex multi-st...
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03/14/2023
It Takes One to Tango but More Make Trouble? In-Context Training with Different Number of Demonstrations
Large language models (LLMs) are capable to perform complex reasoning by...
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06/16/2022
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features
Graph Neural Networks (GNNs) with numerical node features and graph stru...
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10/26/2021
Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
Self-supervised learning (SSL) has achieved great success in a variety o...
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10/26/2021
Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features
For supervised learning with tabular data, decision tree ensembles produ...
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04/14/2020
Particle-based Energetic Variational Inference
We introduce a new variational inference framework, called energetic var...
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10/07/2019