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Type Diversity Enables Transformers to Generalise Compositionally
The compositional generalisation problem has haunted Transformer research for years. Train a seq2seq model on "John drinks coffee" and it learns to translate that just fine. But give it "John drinks coffee on a mat" when only "on...
How SaaS startup guys get first 100 customers first, make fkn $500k ARR fast?
This is a single question with no factual content, no technical details, and no discussion thread included. There is nothing to rewrite.
NVIDIA Personal AI Router Distributes AI Tasks Across Local Compute
NVIDIA released PAIR, Personal AI Router, in beta this week. The tool distributes AI inference requests across multiple machines on a local network, and it does so without requiring changes to the tools you already use. If you are...
General Quantification of Covariate and Concept Shifts
Distribution Shift Is a Broken Promise Every deployed model makes an implicit bet: that the data it sees at inference will look like the data it trained on. When that bet fails, performance degrades silently and sometimes catastro...
Data Scarcity and Model Sparsity: Mixtures-of-Experts Overfit More to Repeated Data
When Running Out of Data Breaks Sparse Models The internet's text is finite. As language model training scales toward and beyond the limits of human-written corpora, repeating data has become standard practice. Muennighoff et al....
Distance generalization in transformers: why bother with positional encoding?
Positional Encoding May Be Hurting Your Transformer Transformers are everywhere, and positional encoding is considered foundational. Every major production model, from Llama to DeepSeek, uses RoPE (Rotary Position Embeddings) to t...
TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription
Automatic Music Transcription for guitar has long been stuck on the wrong side of the difficulty curve compared to piano. Piano AMT hit high note-level accuracy years ago through CRNN models and large paired datasets, but guitar t...
The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement
Modern AI systems can write code, reason through graduate-level science, and plan multi-step research workflows. But every improvement they undergo still requires humans to decide what to fix, build the resources to fix it, and ju...
Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport
Diffusion models and flow-matching models generate images by progressively denoising a noisy sample over a series of timesteps. How that time is allocated across the denoising process, the schedule, has a direct impact on sample q...
Generative Late-Interaction Embeddings For Visual Document Retrieval
Late-interaction retrieval has become the dominant paradigm for searching visual documents. Models like ColPali embed every image patch on a page as a separate vector and score queries against them using MaxSim, a per-token maximu...