r/MachineLearning
r/MachineLearning is a Reddit community for machine learning researchers and enthusiasts. It features discussions on topics like networking at conferences and the long-term value of AI research.
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![The original title is "I Compressed Bad Apple into a 3MB Neural Network [P]"](https://preview.redd.it/h5r0ybpz5ghh1.gif?frame=1&width=140&height=70&auto=webp&s=99152a6a4c15a1a51e20a696f3a52115ce3add98)
The original title is "I Compressed Bad Apple into a 3MB Neural Network [P]"
9d
![The original title is "I created an autonomous boxing benchmark [D]"](https://preview.redd.it/r2i8f52ub8hh1.jpg?width=140&height=78&auto=webp&s=5ea73e9fad702339bb34f2c4c3a5ff60f2b2653b)
The original title is "I created an autonomous boxing benchmark [D]"
10d
![Twin: A Possible Solution to AI Context Rebuilding [P]](https://preview.redd.it/3d8ywukp62hh1.png?width=640&crop=smart&auto=webp&s=05b5d4c32c98bd58fd223fb2bb53e7a80bb8678e)
Twin: A Possible Solution to AI Context Rebuilding [P]
11d
![The original title is "I have trained a model to predict my blood sugar [P]"](https://preview.redd.it/v3bputi1cmgh1.png?width=140&height=91&auto=webp&s=5fcaa20e54e37915fc9d5911c43947f4a7ddb940)
The original title is "I have trained a model to predict my blood sugar [P]"
13d
![Day 9 of self-studying ML — entropy, cross-entropy, and logistic regression notes [D]](https://preview.redd.it/wn6r84l7okgh1.jpg?width=140&height=140&crop=1:1,smart&auto=webp&s=021da52e4d6a491bf1cae1cd37f2a18cbb826097)
Day 9 of self-studying ML — entropy, cross-entropy, and logistic regression notes [D]
14d
![MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]](https://preview.redd.it/9qnhkw960fgh1.png?width=640&crop=smart&auto=webp&s=56e30d9b0ba2781439bd302e229d6a327259f795)
MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]
15d
![AI Security Leaderboard: benchmarking model robustness [P]](https://preview.redd.it/849sof2qs8gh1.jpeg?width=640&crop=smart&auto=webp&s=e35866046cddc5468b5da927b9bf8e5e3eef66c3)
AI Security Leaderboard: benchmarking model robustness [P]
15d
![I implemented the YOLO26n model inference from scratch using ARM64 Assembly Language (No framework) [P]](https://preview.redd.it/wiyelkfpsifh1.jpeg?width=640&crop=smart&auto=webp&s=9ed353f6d1eab4c20efcaa110c0c5f642a6d6e99)
I implemented the YOLO26n model inference from scratch using ARM64 Assembly Language (No framework) [P]
19d
![Real task cost across GPT, Claude, Gemini and Kimi, 10.6x spread on models with only 2x price difference [R]](https://preview.redd.it/7ejtvp684xeh1.png?width=140&height=65&auto=webp&s=10790ba444afd733ece8c54a8b9da99969a86066)
Real task cost across GPT, Claude, Gemini and Kimi, 10.6x spread on models with only 2x price difference [R]
22d
![SkewAdam: A tiered optimizer that cuts MoE state memory by 97% (fits a 6.7B MoE on a 40GB GPU) [R]](https://preview.redd.it/1457xi9fcqeh1.jpg?width=140&height=90&auto=webp&s=879aad6df9e51a2735d91112d01518ff76ba3cbe)
SkewAdam: A tiered optimizer that cuts MoE state memory by 97% (fits a 6.7B MoE on a 40GB GPU) [R]
23d
![Looking for feedback on my GPU-accelerated Snake AI project [P]](https://preview.redd.it/4k0bf6wgtneh1.gif?width=640&crop=smart&s=7309dc4cdba7df36b615ed9025f212c2b34fd4b0)
Looking for feedback on my GPU-accelerated Snake AI project [P]
23d

The original headline is: "AI system Fable 5 reportedly solves major open problem in Algebraic Geometry"
24d
![Tri-Net v2: Open-source implementation of our Scientific Reports paper on unified skin lesion and symptom-based monkeypox detection [R]](https://preview.redd.it/vwax5ludzheh1.png?width=140&height=79&auto=webp&s=25929233532a0110f28de21f8e7a57634c6f791b)
Tri-Net v2: Open-source implementation of our Scientific Reports paper on unified skin lesion and symptom-based monkeypox detection [R]
24d
![Introducing ASCIITermDraw Bench | Testing the ability of VLMs to Generate and Edit ASCII [P]](https://preview.redd.it/9q5cs439mceh1.png?width=140&height=98&auto=webp&s=ebb3f772300fbbd6ecad54b3067b9ea96a92c80f)
Introducing ASCIITermDraw Bench | Testing the ability of VLMs to Generate and Edit ASCII [P]
25d
![Follow up: GPT-2's vocabulary as a hyperbolic tree — 32,070 tokens in a Poincaré ball you can fly through [P]](https://preview.redd.it/o6l1c96lo6eh1.png?width=640&crop=smart&auto=webp&s=92447206205a44b4f473a41cc8557c245d73a7d0)
Follow up: GPT-2's vocabulary as a hyperbolic tree — 32,070 tokens in a Poincaré ball you can fly through [P]
26d
![ASCIITermDraw-Bench | Evaluating VLMs on ASCII Generation and Editing Tasks [P]](https://preview.redd.it/p8w6ju0sk5eh1.png?width=140&height=84&auto=webp&s=dc9838126b956835f1fe68d2840d3e4adbb10dcc)
ASCIITermDraw-Bench | Evaluating VLMs on ASCII Generation and Editing Tasks [P]
26d
![GPT-2 Small’s embedding geometry around “Trump”: discretized vs. continuous nearest neighbours [P]](https://preview.redd.it/tlvz4c3i32eh1.png?width=640&crop=smart&auto=webp&s=aad6aeec9197e26debda00093dd47611e70c5a08)
GPT-2 Small’s embedding geometry around “Trump”: discretized vs. continuous nearest neighbours [P]
26d

The original title is about deep learning for scRNA-seq analysis. Let me rewrite it to be punchy and specific while preserving key facts.
26d
![Seeking collaborators for scaling and independent evaluation of a new recurrent language model architecture (preprint + code) [R]](https://preview.redd.it/b0u6q9a46ndh1.jpg?width=140&height=98&auto=webp&s=dbb02d2e0fc85305a04e37864167c2578891d46c)
Seeking collaborators for scaling and independent evaluation of a new recurrent language model architecture (preprint + code) [R]
29d
![PnP-CoSMo: A Multi-Contrast MRI Reconstruction Framework based on Content/Style Modeling [R]](https://external-preview.redd.it/d6rTpW7131dBgTTGfjDXPAIkblduF91pERLr20qfQH4.jpeg?width=140&height=78&auto=webp&s=efc5027d8347fa1bc645f041300b0979e5c14469)
PnP-CoSMo: A Multi-Contrast MRI Reconstruction Framework based on Content/Style Modeling [R]
29d
![The original title is: "All major robotics and VLA papers, ranked and benchmarked in a single place [P]"](https://preview.redd.it/wvhcgu1q1fdh1.png?width=140&height=88&auto=webp&s=d914b037ae47cf6b529bc66f8af00430d0d590ae)
The original title is: "All major robotics and VLA papers, ranked and benchmarked in a single place [P]"
30d

Building an XGBoost Pipeline for Cross-Domain Conflict Resolution with Explainable AI
30d
![I trained a vision-language model to play Snake, and so can you. [P]](https://external-preview.redd.it/YWcAyMNI6jxa5S-SYFMgIq4qY5VYLAesOmSGvUtU3as.png?width=140&height=70&auto=webp&s=247aa5820e62edcecbb91eb5a961e10ecb0ae66f)
I trained a vision-language model to play Snake, and so can you. [P]
31d
![[P] RL-training Qwen3.6 to RL-train tool using AI models [P]](https://preview.redd.it/hg7ww6ute8dh1.png?width=140&height=75&auto=webp&s=d9c4aa6843cd8b9f2a480a97e0f8469ec80b4d41)
[P] RL-training Qwen3.6 to RL-train tool using AI models [P]
31d