QwenLM / QwenLM/Confident-Decoding
Verify evals on Papers with Code
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- Dominant language
- Python
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Description
Hi,
Niels here from the open-source team at Hugging Face. Congratulations on your work!
I've made the paper and 4 paper-native evaluations available on Papers with Code.
The paper has results on World Knowledge, Long Context, and Mathematics task pages.
The Confident Decoding (Qwen3.5-122B-A10B) results currently rank first on LongBench v2 and Omni-MATH.
Would it be possible to verify these results and let me know if any score, model name, benchmark protocol, or openness metadata should be corrected? The imported rows are tied to the paper or its official release artifacts; comparison-table baselines were not added.
You can also edit the task, methods, project page, and GitHub URL directly from the paper page using your Hugging Face account.
If you'd like to showcase the results in your repository README, you can copy these live leaderboard badges (or use the “Copy PwC badge” button in the Results section):
Kind regards,
Niels
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Open the linked Papers with Code paper page and review its four paper-native evaluations, including the LongBench v2 and Omni-MATH result pages. Compare the score, model name, benchmark protocol, and openness metadata with the paper or official release artifacts; done means correcting any discrepancies or confirming that the imported rows are accurate.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100