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07/20/2023
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets
Evaluation of Large Language Models (LLMs) is challenging because aligni...
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05/24/2023
Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis
Large Language Models (LLMs) have demonstrated great capabilities in sol...
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05/23/2023
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
Large Language Models (LLMs) have shown enhanced capabilities of solving...
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02/28/2023
In-Context Instruction Learning
Instruction learning of Large Language Models (LLMs) has enabled zero-sh...
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02/07/2023
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Recently, Language Models (LMs) instruction-tuned on multiple tasks, als...
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10/06/2022
Retrieval of Soft Prompt Enhances Zero-Shot Task Generalization
During zero-shot inference with language models (LMs), using hard prompt...
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10/06/2022
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners
Meta-training, which fine-tunes the language model (LM) on various downs...
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09/26/2022
Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts
Previous work has shown that there exists a scaling law between the size...
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04/29/2022
TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Language Models (LMs) become outdated as the world changes; they often f...
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10/07/2021
Towards Continual Knowledge Learning of Language Models
Large Language Models (LMs) are known to encode world knowledge in their...
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09/10/2021
