初始化项目，由ModelHub XC社区提供模型

Model: SEGAgentRL/LLDS-A-GSPO-Qwen2.5-3B-Ins
Source: Original Platform

README.md

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