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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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07/31/2023
Virtual Prompt Injection for Instruction-Tuned Large Language Models
We present Virtual Prompt Injection (VPI) for instruction-tuned Large La...
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07/17/2023
AlpaGasus: Training A Better Alpaca with Fewer Data
Large language models (LLMs) obtain instruction-following capability thr...
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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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05/23/2023
Prompting Language-Informed Distribution for Compositional Zero-Shot Learning
The compositional zero-shot learning (CZSL) task aims to recognize unsee...
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05/03/2023
Backdoor Learning on Sequence to Sequence Models
Backdoor learning has become an emerging research area towards building ...
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05/03/2023
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer
Recent studies show that prompt tuning can better leverage the power of ...
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04/12/2023
Dynamic Voxel Grid Optimization for High-Fidelity RGB-D Supervised Surface Reconstruction
Direct optimization of interpolated features on multi-resolution voxel g...
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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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07/09/2021
Beyond Farthest Point Sampling in Point-Wise Analysis
Sampling, grouping, and aggregation are three important components in th...
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08/15/2020