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README.md
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---
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license: apache-2.0
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language:
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- en
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metrics:
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- accuracy
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base_model:
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- Qwen/Qwen2.5-3B-Base
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pipeline_tag: reinforcement-learning
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tags:
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- Search
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- QuestionAnswering
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library_name: transformers
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---
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<h1 align="center">On GRPO Collapse in Search-R1: The Lazy Likelihood-Displacement Death Spiral</h1>
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<p align="center">
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📃 <a href="https://arxiv.org/abs/2512.04220" target="_blank">Paper</a> </a>
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</p>
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## ⚡ Introduction
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**LLDS** is a lightweight likelihood-preserving regularization designed to stabilize **tool-integrated reinforcement learning** (e.g., GRPO / Search-R1 style training).
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It prevents training collapse by regularizing **only when** the likelihood of (good) action decreases, and **only on** the tokens responsible for the decrease.
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- We identify **Lazy Likelihood Displacement (LLD)** as a key mechanism behind collapse in tool-integrated GRPO training.
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- LLDS activates **selectively**: it penalizes likelihood reduction on a *preserving set* (e.g., non-negative-advantage actions).
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- We release our **LLDS-tuned Qwen2.5-3B-Base** checkpoint for searchs-integrated reasoning and QA.
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## 🔍 Tool-Integrated Search Inference (Search-R1 style)
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We support tool-integrated inference using the same workflow as **[Search-R1](https://github.com/PeterGriffinJin/Search-R1)**, where the LLM interacts with a local retrieval server for multi-step reasoning.
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The pipeline consists of two parts:
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1. Launch a local retriever server
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2. Run inference with the LLDS model
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---
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### 1️⃣ Launch the local retrieval server
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Search-R1 recommends running the retriever in a separate environment.
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```bash
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conda activate retriever
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bash retrieval_launch.sh
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```
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### 2️⃣ Run inference with LLDS-R-GRPO-Qwen2.5-3B-Base
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```bash
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conda activate searchr1
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python infer.py
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MODEL_NAME = "<YOUR_ORG>/<YOUR_MODEL_NAME>" # e.g. my-org/LLDS-R-GRPO-Qwen2.5-3B-Base
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question = "Your question here"
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```
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## 📖 Citation
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```
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@article{deng2025grpo,
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title={On GRPO Collapse in Search-R1: The Lazy Likelihood-Displacement Death Spiral},
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author={Deng, Wenlong and Li, Yushu and Gong, Boying and Ren, Yi and Thrampoulidis, Christos and Li, Xiaoxiao},
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journal={arXiv preprint arXiv:2512.04220},
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year={2025}
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}
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```
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