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Collections including paper arxiv:2508.09834

Pruning the Unsurprising: Efficient Code Reasoning via First-Token Surprisal

Paper • 2508.05988 • Published Aug 8 • 19
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

Paper • 2508.07407 • Published Aug 10 • 98
Compressing Chain-of-Thought in LLMs via Step Entropy

Paper • 2508.03346 • Published Aug 5 • 7
Reinforcement Learning in Vision: A Survey

Paper • 2508.08189 • Published Aug 11 • 29

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Paper • 2403.13372 • Published Mar 20, 2024 • 174
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
A Survey of Context Engineering for Large Language Models

Paper • 2507.13334 • Published Jul 17 • 259

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Paper • 2509.02547 • Published Sep 2 • 225
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search

Paper • 2509.25454 • Published Sep 29 • 140
DeMo: Decoupled Momentum Optimization

Paper • 2411.19870 • Published Nov 29, 2024 • 6

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization

Paper • 2508.10395 • Published Aug 14 • 42
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
Causal Attention with Lookahead Keys

Paper • 2509.07301 • Published Sep 9 • 21

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Paper • 2508.18265 • Published Aug 25 • 208
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent

Paper • 2508.05748 • Published Aug 7 • 141
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 160
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL

Paper • 2508.13167 • Published Aug 6 • 129

Peer-Reviewed Articles

AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 160
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Paper • 2403.13372 • Published Mar 20, 2024 • 174
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
Efficient Attention Mechanisms for Large Language Models: A Survey

Paper • 2507.19595 • Published Jul 25 • 6
Mixture of Experts in Large Language Models

Paper • 2507.11181 • Published Jul 15 • 1

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis

Paper • 2404.16754 • Published Apr 25, 2024
LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery

Paper • 2505.02829 • Published May 5
MedQ-Bench: Evaluating and Exploring Medical Image Quality Assessment Abilities in MLLMs

Paper • 2510.01691 • Published Oct 2 • 3

SSRL: Self-Search Reinforcement Learning

Paper • 2508.10874 • Published Aug 14 • 97
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

Pruning the Unsurprising: Efficient Code Reasoning via First-Token Surprisal

Paper • 2508.05988 • Published Aug 8 • 19
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

Paper • 2508.07407 • Published Aug 10 • 98
Compressing Chain-of-Thought in LLMs via Step Entropy

Paper • 2508.03346 • Published Aug 5 • 7
Reinforcement Learning in Vision: A Survey

Paper • 2508.08189 • Published Aug 11 • 29

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Paper • 2508.18265 • Published Aug 25 • 208
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent

Paper • 2508.05748 • Published Aug 7 • 141
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 160
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL

Paper • 2508.13167 • Published Aug 6 • 129

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

Peer-Reviewed Articles

AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs

Paper • 2508.16153 • Published Aug 22 • 160
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Paper • 2403.13372 • Published Mar 20, 2024 • 174
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers

Paper • 2508.14704 • Published Aug 20 • 43
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Paper • 2403.13372 • Published Mar 20, 2024 • 174
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
A Survey of Context Engineering for Large Language Models

Paper • 2507.13334 • Published Jul 17 • 259

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
Efficient Attention Mechanisms for Large Language Models: A Survey

Paper • 2507.19595 • Published Jul 25 • 6
Mixture of Experts in Large Language Models

Paper • 2507.11181 • Published Jul 15 • 1

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Paper • 2509.02547 • Published Sep 2 • 225
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search

Paper • 2509.25454 • Published Sep 29 • 140
DeMo: Decoupled Momentum Optimization

Paper • 2411.19870 • Published Nov 29, 2024 • 6

Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis

Paper • 2404.16754 • Published Apr 25, 2024
LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery

Paper • 2505.02829 • Published May 5
MedQ-Bench: Evaluating and Exploring Medical Image Quality Assessment Abilities in MLLMs

Paper • 2510.01691 • Published Oct 2 • 3

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization

Paper • 2508.10395 • Published Aug 14 • 42
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53
Causal Attention with Lookahead Keys

Paper • 2509.07301 • Published Sep 9 • 21

SSRL: Self-Search Reinforcement Learning

Paper • 2508.10874 • Published Aug 14 • 97
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

Paper • 2508.09834 • Published Aug 13 • 53

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