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Collections including paper arxiv:2510.26583

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 6 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
Ovi: Twin Backbone Cross-Modal Fusion for Audio-Video Generation

Paper • 2510.01284 • Published Sep 30 • 34

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
UME-R1: Exploring Reasoning-Driven Generative Multimodal Embeddings

Paper • 2511.00405 • Published Nov 1 • 5

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model Merging

Paper • 2510.20479 • Published Oct 23 • 11
A Definition of AGI

Paper • 2510.18212 • Published Oct 21 • 34
Video-As-Prompt: Unified Semantic Control for Video Generation

Paper • 2510.20888 • Published Oct 23 • 45

Native Multimodal Models are World Learners 🌍

BAAI/Emu3.5-VisionTokenizer

Updated Oct 31 • 165 • 19
BAAI/Emu3.5-Image

Text-to-Image • 34B • Updated Nov 5 • 278 • 61
BAAI/Emu3.5

Any-to-Any • 34B • Updated Nov 5 • 374 • 162
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models

Paper • 2508.10751 • Published Aug 14 • 28
Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 263
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 159

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
π_RL: Online RL Fine-tuning for Flow-based Vision-Language-Action Models

Paper • 2510.25889 • Published Oct 29 • 64

The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain

Paper • 2509.26507 • Published Sep 30 • 535
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

LightMem: Lightweight and Efficient Memory-Augmented Generation

Paper • 2510.18866 • Published Oct 21 • 110
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders

Paper • 2510.19779 • Published Oct 22 • 60
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

about 6 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 85
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 151
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models

Paper • 2508.10751 • Published Aug 14 • 28
Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 263
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 159

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
Ovi: Twin Backbone Cross-Modal Fusion for Audio-Video Generation

Paper • 2510.01284 • Published Sep 30 • 34

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
UME-R1: Exploring Reasoning-Driven Generative Multimodal Embeddings

Paper • 2511.00405 • Published Nov 1 • 5

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
π_RL: Online RL Fine-tuning for Flow-based Vision-Language-Action Models

Paper • 2510.25889 • Published Oct 29 • 64

Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107
RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model Merging

Paper • 2510.20479 • Published Oct 23 • 11
A Definition of AGI

Paper • 2510.18212 • Published Oct 21 • 34
Video-As-Prompt: Unified Semantic Control for Video Generation

Paper • 2510.20888 • Published Oct 23 • 45

The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain

Paper • 2509.26507 • Published Sep 30 • 535
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

Native Multimodal Models are World Learners 🌍

BAAI/Emu3.5-VisionTokenizer

Updated Oct 31 • 165 • 19
BAAI/Emu3.5-Image

Text-to-Image • 34B • Updated Nov 5 • 278 • 61
BAAI/Emu3.5

Any-to-Any • 34B • Updated Nov 5 • 374 • 162
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

LightMem: Lightweight and Efficient Memory-Augmented Generation

Paper • 2510.18866 • Published Oct 21 • 110
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders

Paper • 2510.19779 • Published Oct 22 • 60
Emu3.5: Native Multimodal Models are World Learners

Paper • 2510.26583 • Published Oct 30 • 107

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