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GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning
Paper • 2602.12099 • Published • 62 -
When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
Paper • 2602.10560 • Published • 31 -
G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic Heuristic Design
Paper • 2602.08253 • Published • 27 -
ROCKET: Rapid Optimization via Calibration-guided Knapsack Enhanced Truncation for Efficient Model Compression
Paper • 2602.11008 • Published • 18
Scott Horwitz
scottrx11
·
AI & ML interests
LLMs
Recent Activity
updated a collection 1 day ago
Collector 2 updated a collection 3 days ago
Collector 2 updated a collection 4 days ago
COLLECTIONOrganizations
None yet
COLLECTION
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AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Paper • 2602.17100 • Published • 4 -
GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant
Paper • 2603.01059 • Published • 1 -
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
Paper • 2603.00618 • Published -
Heterogeneous Agent Collaborative Reinforcement Learning
Paper • 2603.02604 • Published • 199
Collector 2
-
GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning
Paper • 2602.12099 • Published • 62 -
When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
Paper • 2602.10560 • Published • 31 -
G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic Heuristic Design
Paper • 2602.08253 • Published • 27 -
ROCKET: Rapid Optimization via Calibration-guided Knapsack Enhanced Truncation for Efficient Model Compression
Paper • 2602.11008 • Published • 18
COLLECTION
-
AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Paper • 2602.17100 • Published • 4 -
GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant
Paper • 2603.01059 • Published • 1 -
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
Paper • 2603.00618 • Published -
Heterogeneous Agent Collaborative Reinforcement Learning
Paper • 2603.02604 • Published • 199