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LAPO: Leave-One-Turn Attribution for Self-Generated Process Rewards in Multi-Tur

BACKGROUND
1 SIGNALFIRST DETECTED 16 July 2026
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16 Jul
Other feeds and industry voices
13 Apr
SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks

arXiv:2604.08865v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards.

REPORT · WHAT · ArXiv CS.AIOPEN STORY
20 May
What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents

arXiv:2605.19447v1 Announce Type: new Abstract: Reinforcement learning can train LLM agents from sparse task rewards, but long-horizon credit assignment remains challenging: a

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13 May
Adaptive Teacher Exposure for Self-Distillation in LLM Reasoning

arXiv:2605.11458v1 Announce Type: new Abstract: On-policy self-distillation has become a strong recipe for LLM reasoning, where a privileged teacher supervises the student's own

REPORT · WHERE · ArXiv CS.AIOPEN STORY
9 Apr
Scaling Coding Agents via Atomic Skills

arXiv:2604.05013v1 Announce Type: cross Abstract: Current LLM coding agents are predominantly trained on composite benchmarks (e.g., bug fixing), which often leads to

REPORT · HOW · ArXiv CS.AIOPEN STORY
15 Oct
PEARL: Process-Experience Aware Reinforcement Learning for Multi-Turn Agents

arXiv:2610.14636v1 Announce Type: new Abstract: Terminal rewards make multi-turn agents trainable without step-level annotations, but group-relative advantages provide little

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13 Apr
Process Reward Agents for Steering Knowledge-Intensive Reasoning

arXiv:2604.09482v1 Announce Type: new Abstract: Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or

REPORT · WHAT · ArXiv CS.AIOPEN STORY
7 Jul
Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry

arXiv:2607.03702v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong decision-making capabilities in long-horizon interactive tasks, yet they still

REPORT · HOW · ArXiv CS.AIOPEN STORY
22 Jul
Fishing Out Free Riders: Shapley-Based Reward Attribution for Parallel Reasoning via Reinforcement Learning

arXiv:2607.18979v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at multi-step reasoning, yet current parallel reasoning approaches often fail to distinguish the

REPORT · HOW · ArXiv CS.AIOPEN STORY
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