open-source framework · source date 2026-06-01 · 0 comments ·
original1. Problems / challenges / motivations
- Every lab reimplementing PPO/GRPO plumbing wastes effort and makes results incomparable.
- Multi-turn agentic rollouts with tool calls do not fit training loops designed for single-turn completions.
- Rollout throughput becomes the bottleneck without async and load balancing.
2. Key ideas
- A production RL training...
open-source tool · source date 2026-04-01 · 0 comments ·
original1. Problems / challenges / motivations
- RL on agent tasks needs a reward function, and most real tasks have no verifier and no labeled data.
- Hand-crafting reward functions per task is the main cost of applying RL to agents.
- Absolute LLM-judge scores are noisy and poorly calibrated across tasks.
2. Key ideas
- A general-purpose reward function that...
open-source framework · source date 2026-03-29 · 0 comments ·
original1. Problems / challenges / motivations
- RL post-training couples a training engine to a rollout engine, and synchronous coupling leaves accelerators idle.
- Agentic rollouts (tool calls, sandboxes, multi-agent loops) are slow and variable, which makes the coupling worse.
- Agentic RL is often bolted on as a separate framework rather than treated as data...
technical report · source date 2026-02-01 · 0 comments ·
original1. Problems / challenges / motivations
- RLVR works where rewards are verifiable, which excludes most multimodal and open-ended agentic tasks.
- Scaling agentic post-training needs a reward signal that does not depend on hand-written verifiers for every domain.
- Single-agent rollouts limit the diversity of trajectories available to learn from.
2. Key...
peer-reviewed survey · source date 2025-09-02 · 0 comments ·
original1. Problems / challenges / motivations
- Agentic RL work is spread across planning, tool use, memory, reasoning, and perception with no shared taxonomy.
- Standard LLM RL formulations assume a single-step MDP, which does not describe an agent acting over a long horizon with partial observability.
- Environments, benchmarks, and frameworks are fragmented and...