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Collections including paper arxiv:2305.18169

Data augmentation

DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning

Paper • 2303.07864 • Published Mar 14, 2023 • 1
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks

Paper • 2305.13547 • Published May 22, 2023 • 1
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

Paper • 2304.09402 • Published Apr 19, 2023 • 2
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning

Paper • 2305.18169 • Published May 29, 2023 • 1

LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning

Paper • 2305.18169 • Published May 29, 2023 • 1
Quick Starting Dialog Systems with Paraphrase Generation

Paper • 2204.02546 • Published Apr 6, 2022 • 1
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Paper • 2401.16380 • Published Jan 29, 2024 • 49

Continual learning

CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization

Paper • 2310.10134 • Published Oct 16, 2023 • 1
TiC-CLIP: Continual Training of CLIP Models

Paper • 2310.16226 • Published Oct 24, 2023 • 9
In-Context Pretraining: Language Modeling Beyond Document Boundaries

Paper • 2310.10638 • Published Oct 16, 2023 • 29
Controlled Decoding from Language Models

Paper • 2310.17022 • Published Oct 25, 2023 • 15

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 25
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

Diversity of Thought Improves Reasoning Abilities of Large Language Models

Paper • 2310.07088 • Published Oct 11, 2023 • 5
Reverse Chain: A Generic-Rule for LLMs to Master Multi-API Planning

Paper • 2310.04474 • Published Oct 6, 2023 • 2
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques

Paper • 2310.08101 • Published Oct 12, 2023 • 2
Instance Needs More Care: Rewriting Prompts for Instances Yields Better Zero-Shot Performance

Paper • 2310.02107 • Published Oct 3, 2023 • 3

Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 19
Contrastive Prefence Learning: Learning from Human Feedback without RL

Paper • 2310.13639 • Published Oct 20, 2023 • 25
SILC: Improving Vision Language Pretraining with Self-Distillation

Paper • 2310.13355 • Published Oct 20, 2023 • 9
Ranking LLM-Generated Loop Invariants for Program Verification

Paper • 2310.09342 • Published Oct 13, 2023 • 3

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 5
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 19
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

Context compression

In-Context Learning Creates Task Vectors

Paper • 2310.15916 • Published Oct 24, 2023 • 43
When can transformers reason with abstract symbols?

Paper • 2310.09753 • Published Oct 15, 2023 • 3
Improving Length-Generalization in Transformers via Task Hinting

Paper • 2310.00726 • Published Oct 1, 2023 • 1
In-context Autoencoder for Context Compression in a Large Language Model

Paper • 2307.06945 • Published Jul 13, 2023 • 28

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