Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
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2310.13961
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Published
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4
Ensemble
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Diversity of Thought Improves Reasoning Abilities of Large Language Models
Paper • 2310.07088 • Published • 5 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
SAI: Solving AI Tasks with Systematic Artificial Intelligence in Communication Network
Paper • 2310.09049 • Published • 1 -
Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration
Paper • 2310.00280 • Published • 3 -
Efficient RLHF: Reducing the Memory Usage of PPO
Paper • 2309.00754 • Published • 13 -
Reward Model Ensembles Help Mitigate Overoptimization
Paper • 2310.02743 • Published • 1 -
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Paper • 2310.03094 • Published • 12 -
The Consensus Game: Language Model Generation via Equilibrium Search
Paper • 2310.09139 • Published • 12 -
LoRA ensembles for large language model fine-tuning
Paper • 2310.00035 • Published • 2 -
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach
Paper • 2309.02429 • Published • 1 -
Mutual Adversarial Training: Learning together is better than going alone
Paper • 2112.05005 • Published • 1 -
Cross-Domain Ensemble Distillation for Domain Generalization
Paper • 2211.14058 • Published • 1 -
Stabilizing RLHF through Advantage Model and Selective Rehearsal
Paper • 2309.10202 • Published • 9 -
Large Language Models are not Fair Evaluators
Paper • 2305.17926 • Published • 1 -
SCALE: Synergized Collaboration of Asymmetric Language Translation Engines
Paper • 2309.17061 • Published • 1 -
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles
Paper • 2306.01705 • Published • 1 -
Skeleton-of-Thought: Large Language Models Can Do Parallel Decoding
Paper • 2307.15337 • Published • 36 -
i-Code Studio: A Configurable and Composable Framework for Integrative AI
Paper • 2305.13738 • Published • 1 -
EcoAssistant: Using LLM Assistant More Affordably and Accurately
Paper • 2310.03046 • Published • 5 -
Are Pre-trained Language Models Useful for Model Ensemble in Chinese Grammatical Error Correction?
Paper • 2305.15183 • Published • 1 -
A Mixture-of-Expert Approach to RL-based Dialogue Management
Paper • 2206.00059 • Published • 1 -
T5APR: Empowering Automated Program Repair across Languages through Checkpoint Ensemble
Paper • 2309.15742 • Published • 1 -
OpenAGI: When LLM Meets Domain Experts
Paper • 2304.04370 • Published • 1 -
Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents
Paper • 2306.03314 • Published • 2 -
Unleashing Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration
Paper • 2307.05300 • Published • 18 -
Communicative Agents for Software Development
Paper • 2307.07924 • Published • 3 -
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs
Paper • 2311.05657 • Published • 27 -
Improving Online Continual Learning Performance and Stability with Temporal Ensembles
Paper • 2306.16817 • Published • 1 -
Neural Architecture for Online Ensemble Continual Learning
Paper • 2211.14963 • Published • 1 -
Differentiable Model Selection for Ensemble Learning
Paper • 2211.00251 • Published • 1 -
AutoDES: AutoML Pipeline Generation of Classification with Dynamic Ensemble Strategy Selection
Paper • 2201.00207 • Published • 1 -
Model Zoo: A Growing "Brain" That Learns Continually
Paper • 2106.03027 • Published • 1 -
TAME: Task Agnostic Continual Learning using Multiple Experts
Paper • 2210.03869 • Published • 1 -
MPCFormer: fast, performant and private Transformer inference with MPC
Paper • 2211.01452 • Published • 1 -
Model Spider: Learning to Rank Pre-Trained Models Efficiently
Paper • 2306.03900 • Published • 1 -
Plug-and-Play Knowledge Injection for Pre-trained Language Models
Paper • 2305.17691 • Published • 1 -
Scaling Expert Language Models with Unsupervised Domain Discovery
Paper • 2303.14177 • Published • 2 -
SwitchGPT: Adapting Large Language Models for Non-Text Outputs
Paper • 2309.07623 • Published • 1 -
Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models
Paper • 2311.08692 • Published • 12 -
A Neural Scaling Law from Lottery Ticket Ensembling
Paper • 2310.02258 • Published • 1 -
Octopus v4: Graph of language models
Paper • 2404.19296 • Published • 117