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2.41 kB
| license: apache-2.0 | |
| language: | |
| - zh | |
| - en | |
| pretty_name: ScholarSearchAgent Auxiliary Models | |
| tags: | |
| - information-retrieval | |
| - reranking | |
| - text-classification | |
| - lora | |
| - academic-search | |
| # ScholarSearchAgent Auxiliary Models | |
| This dataset repository hosts the trained auxiliary model artifacts used by | |
| ScholarSearchAgent, an intelligent academic paper search and recommendation | |
| system for complex research queries. | |
| Source code: <https://github.com/Kaedeser/ScholarSearchAgent> | |
| ## Download And Restore | |
| The complete model bundle is stored as 200 MiB archive parts named | |
| `ScholarSearchAgentAuxiliaryModel_20260723.tar.part0001`, | |
| `ScholarSearchAgentAuxiliaryModel_20260723.tar.part0002`, and so on. Download | |
| all parts in numerical order, concatenate them, verify the SHA-256 value, then | |
| extract the resulting TAR archive. | |
| PowerShell: | |
| ```powershell | |
| Get-ChildItem "ScholarSearchAgentAuxiliaryModel_20260723.tar.part*" | | |
| Sort-Object Name | | |
| Get-Content -AsByteStream | | |
| Set-Content -AsByteStream "ScholarSearchAgentAuxiliaryModel_20260723.tar" | |
| Get-FileHash "ScholarSearchAgentAuxiliaryModel_20260723.tar" -Algorithm SHA256 | |
| tar -xf "ScholarSearchAgentAuxiliaryModel_20260723.tar" | |
| ``` | |
| Expected SHA-256: | |
| ```text | |
| c15830db9b3c126d584b1ffbdef17cd70a4101d20470ad78661eb883b4fe4a46 | |
| ``` | |
| ## Included Models | |
| | Directory after extraction | Purpose | Model form | Reported result | | |
| | --- | --- | --- | | |
| | `models/query_gate_biobert` | Detect whether a query should enter the academic-search pipeline | BioBERT sequence classifier | Test accuracy: 0.997143 | | |
| | `models/intent_biobert` | Classify academic search intent | BioBERT sequence classifier | See packaged training metadata | | |
| | `models/selector_reranker` | Rerank recalled paper candidates | Sentence Transformers CrossEncoder | F1: 88.81% | | |
| | `models/crawler_strategy_lora` | Select section-expansion strategies | Qwen2.5-3B-Instruct LoRA adapter | Section F1: 0.3007 | | |
| The crawler strategy artifact is a LoRA adapter. The public | |
| `Qwen2.5-3B-Instruct` base model is not redistributed in this repository and | |
| must be obtained separately under its original license. | |
| ## Data And Privacy | |
| The archive contains model weights, tokenizer/configuration files, and training | |
| metadata required for inference. It does not contain API keys, passwords, | |
| private endpoints, raw training datasets, source-code history, or participant | |
| identity information. | |