-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 22 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 145 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2408.15998
-
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution
Paper • 2412.15213 • Published • 25 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 41 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 117 -
Autoregressive Video Generation without Vector Quantization
Paper • 2412.14169 • Published • 14
-
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Paper • 2408.15998 • Published • 84 -
General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
Paper • 2409.01704 • Published • 83 -
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
Paper • 2408.06195 • Published • 64 -
Self-Reflection in LLM Agents: Effects on Problem-Solving Performance
Paper • 2405.06682 • Published • 3
-
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Paper • 2408.11039 • Published • 58 -
Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming
Paper • 2408.16725 • Published • 52 -
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Paper • 2408.15998 • Published • 84
-
What matters when building vision-language models?
Paper • 2405.02246 • Published • 101 -
MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data
Paper • 2406.18790 • Published • 33 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
-
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 98 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
-
PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
Paper • 2408.07547 • Published • 8 -
DeepSpeak Dataset v1.0
Paper • 2408.05366 • Published • 12 -
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Paper • 2408.15998 • Published • 84 -
Zero-shot Cross-lingual Voice Transfer for TTS
Paper • 2409.13910 • Published • 8