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Sun, May 242 dispatches

#0829
#0829Other r/MachineLearning6 days ago
`PapersWithCode` adds multi-metric leaderboards and paper lineage
50radar
PapersWithCodeAI benchmark site — tracks SOTA, code, and leaderboards
Leaderboards can now show multiple metrics like accuracy and speed. It is useful for model shortlisting, not just SOTA browsing.
- 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.
Source: www.reddit.com/r/MachineLearning/comments/1tmawv5/papersRead original →
50radar
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#0828
#0828Other r/MachineLearning7 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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FIG-8281:1

Mon, May 181 dispatches

#0827
#0827Other r/MachineLearning2 weeks ago
Hugging Face revives `PapersWithCode` with AI-parsed leaderboards
50radar
PapersWithCodeAI paper tracker — links code and benchmarks
The rebuilt site tracks trending papers, methods, citations, repos, artifacts, and benchmark results. Useful for model scouting, but still manually verified and early-stage.
- Default ranking uses GitHub star velocity, so it surfaces research projects gaining developer attention, not just citation-heavy papers.
- Coverage starts with high-impact items like Qwen 3.5, RF-DETR, DINOv3, MTEB, Open ASR Leaderboard, and coding-agent benchmarks.
- Paper pages auto-link GitHub repos, project URLs, artifacts, PDFs, and external non-Arxiv papers; multiple repos per paper are supported.
- Leaderboards exist by benchmark and domain, including MMTEB, COCO val 2017, and Terminal Bench; handy for fast model/vendor filtering.
- Result extraction uses AI agents, but verification is still manual. Treat it as a shortlist generator, not a source of record yet.
Source: www.reddit.com/r/MachineLearning/comments/1tgmwqr/reviviRead original →
50radar
PHOTO
FIG-8271:1

`PapersWithCode` adds multi-metric leaderboards and paper lineage

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

Hugging Face revives `PapersWithCode` with AI-parsed leaderboards