… The following papers were recommended by the Semantic Scholar API PRAISE: Prefix-Based Rollout Reuse in Agentic Search Training 2026 Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Model 2026 Accelerating RL Post-Training Rollouts via System-Integ… …
Papers arxiv:2605.01214 Agentic AI Systems Should Be Designed as Marginal Token Allocators Published on May 2 Submitted by siqi zhu on May 5 University of Illinois at Urbana-Champaign Authors: Siqi Zhu Abstract Agentic AI systems should be evaluated as marginal token allocation economies rather tha… …
… View arXiv page View PDF Project page Add to collection Community ClawGym: full-lifecycle framework for Claw-style personal agents 1️⃣ Data : ClawGym-SynData — 13.5K filtered tasks, persona-driven intents × skill-grounded ops, with mock workspaces & hybrid verification 2️⃣ Training : ClawGym-Agents… …
… AI-generated summary Asynchronous reinforcement learning improves rollout throughput for large language model agents by decoupling sample generation from policy optimization, but it also introduces a critical failure mode for PPO-style off-policy correction . …
… On top of this harness, On-policy Data Evolution ODE runs a closed-loop data generator that refines itself across rounds from rollouts of the policy being trained. …
… The following papers were recommended by the Semantic Scholar API Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM Agents 2026 DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents 2026 Co-Evolution of Policy and Internal Reward for Language A… …
… Interesting breakdown of this paper on arXivLens: https://arxivlens.com/PaperView/Details/tmas-scaling-test-time-compute-via-multi-agent-synergy-682-9aa2c46a Covers the executive summary, detailed methodology, and practical applications. …
… The following papers were recommended by the Semantic Scholar API IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning 2026 Self-Induced Outcome Potential: Turn-Level Credit Assignment for Agents without Verifiers 2026 TIPS: Turn-Level Information-Potential Reward Shaping f… …
… View arXiv page View PDF Add to collection Community seeing how much the gains hinge on draft initialization and keeping drafts short, it looks like the method pays off most when the speculative drafts stay close to the current rollout distribution. my question is: how does speculative decoding beh… …
… Unlike in virtual AI agents, the timing of decisions, actions and tool calls is important in a physical world that does not pause for reasoning. …
