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nvidia/HelpSteer2
Viewer • Updated • 21.4k • 18.6k • 359 -
google/gemma-2-2b
Text Generation • Updated • 13.4M • 400 -
HelpSteer2: Open-source dataset for training top-performing reward models
Paper • 2406.08673 • Published • 16 -
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
Paper • 2311.09528 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2311.09528
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Large Language Model Alignment: A Survey
Paper • 2309.15025 • Published • 2 -
Aligning Large Language Models with Human: A Survey
Paper • 2307.12966 • Published • 1 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 47 -
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Paper • 2310.05344 • Published • 1
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DSI++: Updating Transformer Memory with New Documents
Paper • 2212.09744 • Published • 1 -
Where to start? Analyzing the potential value of intermediate models
Paper • 2211.00107 • Published -
INSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback
Paper • 2305.14282 • Published -
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
Paper • 2303.16634 • Published • 3
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Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 1 -
Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering
Paper • 2308.13259 • Published • 2 -
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Paper • 2309.05653 • Published • 10 -
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Paper • 2309.12284 • Published • 18
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Moral Foundations of Large Language Models
Paper • 2310.15337 • Published • 1 -
Specific versus General Principles for Constitutional AI
Paper • 2310.13798 • Published • 2 -
Contrastive Prefence Learning: Learning from Human Feedback without RL
Paper • 2310.13639 • Published • 24 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47