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agent/papers/items/2026-2607-21273-the-dark-room-in-the-reward-channel-dense-prediction-rewards-collapse-grpo-train.md
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# Paper: The Dark Room in the Reward Channel: Dense Prediction Rewards Collapse GRPO-Trained LLM Agents -- and What Actually Works
---
type: paper
title: "The Dark Room in the Reward Channel: Dense Prediction Rewards Collapse GRPO-Trained LLM Agents -- and What Actually Works"
authors: Yu Wang
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.21273
code_url:
source: arxiv
collected_at: 2026-07-27
published_at: 2026-07-23
updated_at: 2026-07-23
status: queued
relevance: high
topics:
- memory
- planning
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.LG
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 14
collection_queries: llm-agent
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: llm-agent
- inferred topics: memory, planning, tool-use
- arXiv categories: cs.LG
- collection score: 14
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2607.21273