`PapersWithCode` adds multi-metric leaderboards and paper lineage

Leaderboards can now show multiple metrics like accuracy and speed. It is useful for model shortlisting, not just SOTA browsing.

[ KEY POINTS ]

Open ASR Leaderboard now supports WER and RTFx. Accuracy and inference speed can be compared in one view.
COCO object detection adds FPS next to mAP. That helps filter models for demos, mobile, or latency-bound products.
Non-Arxiv papers can be submitted from GitHub, blogs, BioRxiv, and more. AI enriches them with tags, repos, and evals.
Paper lineage banners and method citation pages make it easier to trace how architectures evolve across papers.

Originalwww.reddit.com/r/MachineLearning/comments/1tmawv5/paperswithcode_new_features_week_1_p/Read original →

// related

#0001
#0001Other GeekNewsyesterday
Use HTML `<dl>` for Name-Value UI Patterns
40radar
<dl> is the semantic HTML element for name-value pairs. It fits amenities, invoices, specs, and glossary UIs, so it is a small but useful accessibility and markup habit.
- <dl> represents a list of name-value pairs, not just a dictionary-style glossary.
- Good fits include amenities, billing line items, technical terms, and product spec rows where labels and values repeat.
- Using <dt> for names and <dd> for values keeps UI markup semantic without adding custom div-heavy structure.
Source: news.hada.io/topic?id=29821Read original →
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40radar
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#0002
#0002Other r/MachineLearning2 days ago
Vision LLMs vs. OCR for PDF Q&A: OCR Still Wins on Cost and Accuracy
60radar
For complex PDF Q&A, vision LLMs are pricier and less accurate than OCR pipelines. Stick with OCR for better cost-performance and reliability.
- The native vision LLM approach was the most expensive at $0.2552/query and ranked 5th in accuracy (52.0%) out of six methods tested.
- Vision models underperformed on chart- and table-heavy pages, the very area they were expected to excel in. Premium OCR handled these better.
- The vision LLM had a 7% intrinsic failure rate that persisted after retries, while OCR-based pipelines showed 0% failure, indicating higher reliability.
Source: www.reddit.com/r/MachineLearning/comments/1tm0cqg/visionRead original →
60radar
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#0003
#0003Other GeekNews2 days ago
`Electrobun 2.0` to Split from `Bun` After Rust Rewrite
40radar
ElectrobunDesktop app framework — packages native apps with web tech
Desktop app runtime dependencies are changing, with less reliance on Bun. Useful only if you are evaluating Electron alternatives; otherwise low urgency.
- Electrobun 2.0 is moving toward a Rust rewrite and reduced Bun dependency, changing its runtime structure.
- The split was influenced by concerns that Anthropic lacks enough human review, staged rollout, and stabilization process.
- This is a niche signal for desktop app stacks: wait for migration notes before building production workflows on it.
Source: news.hada.io/topic?id=29815Read original →
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40radar
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`PapersWithCode` adds multi-metric leaderboards and paper lineage

// related

Use HTML `<dl>` for Name-Value UI Patterns

Vision LLMs vs. OCR for PDF Q&A: OCR Still Wins on Cost and Accuracy

`Electrobun 2.0` to Split from `Bun` After Rust Rewrite