CS & AI Paper Deep Explainer
Turn dense arXiv machine-learning papers into clear engineering notes: equations translated to plain language, pseudocode logic, model architecture, and links back to the source code.
∑ → text
equations explained
upload supported
code
source traceback
Structured explanation
Ready when you are.
- Problem
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- Method
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- Key equations → plain language
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- Algorithm / pseudocode
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- Model architecture
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- Key results & benchmarks
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- Code / source links
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- Limitations
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Plain-language summary
Trending AI papers on arXiv
The hottest recent CS/AI papers, refreshed from our ingest. Open one and paste it above to explain.
Syn-Omni: Structured Specialization and Progressive Collaboration for Omnimodal Embeddings
2610.12256
Caught in the Act: Probes Effectively Detect Sabotage and Catch Unverbalized Deception
2610.12445
Rounding in Preconditioner Space: Redesigning 4-bit AdamW Optimizer-State Quantization
2610.12444
Long Text to Predictive Features: LLM-Guided Blockwise Feature Engineering via Executable Program Search
2610.12390
Searching for "Harmful Refusal": A Psychometric Audit of an AI Safety Benchmark
2610.12409
Bilevel optimization for data-driven learning of Koopman embeddings using kernel-based autoencoders
2610.12370
Cited but Not Consulted: A Counterfactual Audit of Legal Chain-of-Thought Faithfulness
2610.12361
Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition
2610.12341
Read arXiv like an engineer
Explanations are generated by AI models (DeepSeek or GPT) — verify against the paper.
Equations in plain words
Translates the paper's core equations into natural language: what each symbol means and what the formula computes.
Pseudocode & architecture
Breaks the main algorithm into step-by-step logic and maps the model architecture and data flow.
Trace the code
Surfaces official repository, dataset, and source links mentioned in the paper so you can jump straight to the implementation.
How it works
From a dense arXiv paper to engineering notes in seconds.
01
Paste or upload
Paste an abstract/section or drop a paper PDF — text is extracted in your browser.
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Explain
The model translates equations, breaks down the algorithm, and maps the architecture.
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Copy into your notes
Copy or download the structured explanation for reading logs, reproductions, or reviews.
FAQ
Does it replace reading the paper?
No. It is a reading aid. Verify every equation, result, and claim against the original paper, especially for reproduction.
Can it read a PDF?
Yes. PDF text is extracted locally in your browser and sent as text; scanned image-only PDFs without a text layer will not work.
How are equations handled?
The model explains the paper's equations in words and keeps symbols/variable names unchanged. It is instructed not to invent equations that are not in the text.