Collections

17

Creative Robot Tool Use with Large Language Models

Paper • 2310.13065 • Published Oct 19, 2023 • 8
CodeCoT and Beyond: Learning to Program and Test like a Developer

Paper • 2308.08784 • Published Aug 17, 2023 • 5
Lemur: Harmonizing Natural Language and Code for Language Agents

Paper • 2310.06830 • Published Oct 10, 2023 • 30
CodePlan: Repository-level Coding using LLMs and Planning

Paper • 2309.12499 • Published Sep 21, 2023 • 73

6

A Zero-Shot Language Agent for Computer Control with Structured Reflection

Paper • 2310.08740 • Published Oct 12, 2023 • 14
AgentTuning: Enabling Generalized Agent Abilities for LLMs

Paper • 2310.12823 • Published Oct 19, 2023 • 35
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Paper • 2308.10848 • Published Aug 21, 2023 • 1
CLEX: Continuous Length Extrapolation for Large Language Models

Paper • 2310.16450 • Published Oct 25, 2023 • 9

Creative Robot Tool Use with Large Language Models

CodeCoT and Beyond: Learning to Program and Test like a Developer

Lemur: Harmonizing Natural Language and Code for Language Agents

CodePlan: Repository-level Coding using LLMs and Planning

A Zero-Shot Language Agent for Computer Control with Structured Reflection

AgentTuning: Enabling Generalized Agent Abilities for LLMs

AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

CLEX: Continuous Length Extrapolation for Large Language Models

Chain-of-Thought Reasoning Without Prompting

How to Train Data-Efficient LLMs

BitDelta: Your Fine-Tune May Only Be Worth One Bit

A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

CodePlan: Repository-level Coding using LLMs and Planning

MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning

Self-Rewarding Language Models

ReFT: Reasoning with Reinforced Fine-Tuning

Tuning Language Models by Proxy

TrustLLM: Trustworthiness in Large Language Models

Challenges and Opportunities of Using Transformer-Based Multi-Task Learning in NLP Through ML Lifecycle: A Survey

Understanding and Improving Information Transfer in Multi-Task Learning

Improving Multi-task Learning via Seeking Task-based Flat Regions

Improvable Gap Balancing for Multi-Task Learning

Ziya2: Data-centric Learning is All LLMs Need

Co-training and Co-distillation for Quality Improvement and Compression of Language Models

MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning

ADaPT: As-Needed Decomposition and Planning with Language Models

CodeFusion: A Pre-trained Diffusion Model for Code Generation

MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning

A Survey on Language Models for Code

Magicoder: Source Code Is All You Need

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

QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

LoRA ensembles for large language model fine-tuning

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

Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Evaluating the Robustness to Instructions of Large Language Models