Public story · 2026-03-03 · source-backed

Memory-R1: RL-Based Agent Memory Management

Issue

2026-03-03

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source-backed

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passed

Story

Two specialized RL agents — Memory Manager (ADD/UPDATE/DELETE operations) and Answer Agent — fine-tuned with PPO and GRPO. With only 152 training QA pairs, outperforms baselines across three benchmarks. Directly applicable to persistent agent memory systems. arXiv 2508.19828

GRPO competes with PPO / Shared entities / Same source domain / Shared topic / Earlier coverage
EMPO2: Memory-Augmented Agent (ICLR 2026)
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO, Memory; reported by the same outlet (arxiv.org).
Unsloth released GRPO / Shared entity: GRPO / What happened next / Tension
Unsloth makes single-H100 long-context RL fine-tuning actually tractable.
Linked by a graph relationship (Unsloth released GRPO); both cover GRPO; picks up the GRPO thread on 2026-06-20.
GRPO competes with PPO / Shared entity: GRPO / Same source domain / Shared topic / What happened next
A 2B-Parameter Model Learns When to Stop Answering
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO; reported by the same outlet (arxiv.org).
GRPO competes with PPO / Shared entity: PPO / Same source domain / Shared topic / What happened next / Tension
Dark Souls Learning Environment: five methods, 22 bosses, every RL agent scores essentially zero.
Linked by a graph relationship (GRPO competes with PPO); both cover PPO; reported by the same outlet (arxiv.org).
GRPO competes with PPO / Shared entity: GRPO / Same source domain / Shared topic / What happened next
Sleeper Cell Backdoors in Fine-Tuned Models: Poisoned LoRAs Pass All Benchmarks
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO; reported by the same outlet (arxiv.org).
Off-Context GRPO Fixes RLVR's Zero-Reward Blind Spot
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO; reported by the same outlet (arxiv.org).
RetroAgent: Dual Intrinsic Feedback.
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO; reported by the same outlet (arxiv.org).
HCAPO: Hindsight Credit Assignment for Sparse-Reward Agent RL.
Linked by a graph relationship (GRPO competes with PPO); both cover GRPO; reported by the same outlet (arxiv.org).

Source trail

arXiv 2508.19828

Entities

Answer Agent Based Agent Memory Management Two Directly GRPO Memory Memory Manager PPO UPDATE

Provenance

Canonical issue: Ramsay Research Agent — 2026-03-03
AI generated: no
Story unit: 2026-03-03-memory-r1-rl-based-agent-memory-management
Labels: source-backed, canonical briefing excerpt

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Memory-R1: RL-Based Agent Memory Management

Story

Related stories

EMPO2: Memory-Augmented Agent (ICLR 2026)

Unsloth makes single-H100 long-context RL fine-tuning actually tractable.

A 2B-Parameter Model Learns When to Stop Answering

Dark Souls Learning Environment: five methods, 22 bosses, every RL agent scores essentially zero.

Sleeper Cell Backdoors in Fine-Tuned Models: Poisoned LoRAs Pass All Benchmarks

Off-Context GRPO Fixes RLVR's Zero-Reward Blind Spot

RetroAgent: Dual Intrinsic Feedback.

HCAPO: Hindsight Credit Assignment for Sparse-Reward Agent RL.

Source trail

Entities

Provenance

Memory-R1: RL-Based Agent Memory Management

Story

Related stories

EMPO2: Memory-Augmented Agent (ICLR 2026)

Unsloth makes single-H100 long-context RL fine-tuning actually tractable.

A 2B-Parameter Model Learns When to Stop Answering

Dark Souls Learning Environment: five methods, 22 bosses, every RL agent scores essentially zero.

Sleeper Cell Backdoors in Fine-Tuned Models: Poisoned LoRAs Pass All Benchmarks

Off-Context GRPO Fixes RLVR's Zero-Reward Blind Spot

RetroAgent: Dual Intrinsic Feedback.

HCAPO: Hindsight Credit Assignment for Sparse-Reward Agent RL.

Source trail

Entities

Provenance