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FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 29 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 42 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 55 -
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
Paper • 2405.18991 • Published • 12
Collections
Discover the best community collections!
Collections including paper arxiv:2508.16153
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LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries
Paper • 2508.15760 • Published • 44 -
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
Paper • 2508.01780 • Published • 18 -
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Paper • 2304.08244 • Published • 1 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131
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Training a Foundation Model for Materials on a Budget
Paper • 2508.16067 • Published • 2 -
PosterGen: Aesthetic-Aware Paper-to-Poster Generation via Multi-Agent LLMs
Paper • 2508.17188 • Published • 15 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 28
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InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Paper • 2508.18265 • Published • 179 -
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent
Paper • 2508.05748 • Published • 122 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 122
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24
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rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 97 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
Beyond Pass@1: Self-Play with Variational Problem Synthesis Sustains RLVR
Paper • 2508.14029 • Published • 117 -
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Paper • 2508.18265 • Published • 179
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AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 135 -
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Paper • 2508.14704 • Published • 42 -
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
Paper • 2508.09834 • Published • 52
-
FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 29 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 42 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 55 -
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
Paper • 2405.18991 • Published • 12
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24
-
LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries
Paper • 2508.15760 • Published • 44 -
LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
Paper • 2508.01780 • Published • 18 -
API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs
Paper • 2304.08244 • Published • 1 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131
-
rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 97 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
Beyond Pass@1: Self-Play with Variational Problem Synthesis Sustains RLVR
Paper • 2508.14029 • Published • 117 -
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Paper • 2508.18265 • Published • 179
-
Training a Foundation Model for Materials on a Budget
Paper • 2508.16067 • Published • 2 -
PosterGen: Aesthetic-Aware Paper-to-Poster Generation via Multi-Agent LLMs
Paper • 2508.17188 • Published • 15 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 28
-
InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Paper • 2508.18265 • Published • 179 -
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent
Paper • 2508.05748 • Published • 122 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 122
-
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 131 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 135 -
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Paper • 2508.14704 • Published • 42 -
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
Paper • 2508.09834 • Published • 52