Update README.md
Browse files
README.md
CHANGED
|
@@ -43,7 +43,7 @@ dataset_info:
|
|
| 43 |
**OpenResearcher** is a fully open agentic large language model (30B-A3B) designed for **long-horizon deep research** scenarios. It achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https://huggingface.co/spaces/Tevatron/BrowseComp-Plus), surpassing performance of `GPT-4.1`, `Claude-Opus-4`, `Gemini-2.5-Pro`, `DeepSeek-R1` and `Tongyi-DeepResearch`. It also demonstrates **leading performance** across a range of deep research benchmarks, including BrowseComp, GAIA, WebWalkerQA, and xbench-DeepSearch. We **fully open-source** the training and evaluation recipe—including data, model, training methodology, and evaluation framework for everyone to progress deep research.
|
| 44 |
|
| 45 |
## OpenResearcher Corpus
|
| 46 |
-
This dataset contains a carefully curated ~11B-tokens corpus, which serves as an offline search engine for our data generation process, eliminating the need for external Search APIs. Details on the corpus curation process are available in our [blog](https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link).
|
| 47 |
|
| 48 |
## Format
|
| 49 |
Each row in the dataset contains the following fields:
|
|
@@ -52,10 +52,4 @@ Each row in the dataset contains the following fields:
|
|
| 52 |
+ **url** (string): The source URL where the document was retrieved from.
|
| 53 |
|
| 54 |
## How to use this dataset?
|
| 55 |
-
You can use
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
|
|
|
| 43 |
**OpenResearcher** is a fully open agentic large language model (30B-A3B) designed for **long-horizon deep research** scenarios. It achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https://huggingface.co/spaces/Tevatron/BrowseComp-Plus), surpassing performance of `GPT-4.1`, `Claude-Opus-4`, `Gemini-2.5-Pro`, `DeepSeek-R1` and `Tongyi-DeepResearch`. It also demonstrates **leading performance** across a range of deep research benchmarks, including BrowseComp, GAIA, WebWalkerQA, and xbench-DeepSearch. We **fully open-source** the training and evaluation recipe—including data, model, training methodology, and evaluation framework for everyone to progress deep research.
|
| 44 |
|
| 45 |
## OpenResearcher Corpus
|
| 46 |
+
This dataset contains a carefully curated **~11B-tokens** corpus, which serves as an offline search engine for our data generation process, eliminating the need for external Search APIs. Details on the corpus curation process are available in our [blog](https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link).
|
| 47 |
|
| 48 |
## Format
|
| 49 |
Each row in the dataset contains the following fields:
|
|
|
|
| 52 |
+ **url** (string): The source URL where the document was retrieved from.
|
| 53 |
|
| 54 |
## How to use this dataset?
|
| 55 |
+
You can use this dataset together with its embeddings to build an offline search engine.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|