-
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 143 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 11 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 50 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 44
Collections
Discover the best community collections!
Collections including paper arxiv:2409.06595
-
The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines
Paper • 2408.01050 • Published • 8 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 33 -
Towards a Unified View of Preference Learning for Large Language Models: A Survey
Paper • 2409.02795 • Published • 72 -
Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance
Paper • 2409.04593 • Published • 22
-
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Paper • 2408.00765 • Published • 12 -
Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent
Paper • 2407.21646 • Published • 18 -
LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
Paper • 2408.04284 • Published • 22 -
Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability
Paper • 2408.07852 • Published • 14
-
GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models
Paper • 2406.14550 • Published • 4 -
Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 55 -
Meta Prompting for AGI Systems
Paper • 2311.11482 • Published • 3 -
Symbolic Learning Enables Self-Evolving Agents
Paper • 2406.18532 • Published • 11
-
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 53 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 32 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 6 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 68