SEGAgentRL

non-profit

AI & ML interests

We target improved agent reinforcement learning in terms of stability (S), efficiency (E), and generalization (G).

SEGAgentRL 's models 10

SEGAgentRL/LLDS-A-GRPO-Llama3.2-3B-Base-MA

Reinforcement Learning • 4B • Updated Jan 16 • 1

SEGAgentRL/LLDS-A-GRPO-Qwen2.5-3B-Ins

Reinforcement Learning • 3B • Updated Jan 15

SEGAgentRL/LLDS-R-GRPO-Qwen2.5-3B-Base

Reinforcement Learning • 3B • Updated Jan 15 • 2 • 1

SEGAgentRL/LLDS-R-GSPO-Qwen2.5-3B-Ins

Reinforcement Learning • 3B • Updated Jan 15 • 4 • 1

SEGAgentRL/LLDS-A-GSPO-Qwen2.5-3B-Ins

Reinforcement Learning • 3B • Updated Jan 15 • 1 • 1

SEGAgentRL/LLDS-R-GRPO-Qwen2.5-3B-Ins

Reinforcement Learning • 3B • Updated Jan 15 • 2 • 1

SEGAgentRL/LLDS-A-GRPO-Qwen2.5-3B-Base

Reinforcement Learning • 3B • Updated Jan 15 • 1

SEGAgentRL/LLDS-A-GRPO-Qwen2.5-3B-Base-MA

Reinforcement Learning • 3B • Updated Jan 15 • 3 • 1

SEGAgentRL/LLDS-A-GRPO-Qwen2.5-7B-Base

Reinforcement Learning • 8B • Updated Jan 15 • 2 • 2

SEGAgentRL/LLDS-A-GRPO-Qwen2.5-7B-Ins

Reinforcement Learning • 8B • Updated Jan 15 • 3 • 2