AI News · Models & Methods
Machine learning news: training methods, data, evaluation and ML engineering in production.
373 stories · Updated
373 stories
Scientific foundation models (SciFMs) have achieved remarkable performance on a wide range of PDEs, including the ability to efficiently adapt to unseen data distributions with additional finetuning. As with all neural architectures, finetuning such models comes with the risk of catastrophic forgetting, whereby…
Training a large language model is compute-bound, and current recipes divide the work between optimizers by hand: orthogonalized momentum for attention and MLP matrices, Adam-style updates for the rest. This division rests on human priors about which layer type deserves which geometry, and it fixes a single global…
We study first-order regret guarantees for adversarial bandits with a fixed, known directed feedback graph. For strongly observable graphs, [ACBDK15] establishes a minimax regret of $\widetilde{\Theta}(\sqrt{\alpha T})$, where $\alpha$ denotes the independence number of the graph and $T$ denotes the horizon. On the…
High-dimensional tensors are ubiquitous in real-world applications but lead to massive storage overhead. Functional tensor decomposition addresses this by employing neural networks to map element coordinates to tensor cores, significantly reducing the parameters for data compression. However, existing functional…
Atomistic simulations help researchers understand how molecules and materials behave, from chemical reactions and phase transitions to mechanical failure. These...
As AI adoption expands globally, people across languages and cultures are using it in more aspects of their daily lives. General-purpose language models serve...
Explore how to audit and rebuild Datalab's OmniParseBench, test parser ranking certainty with document-level bootstrapping, and evaluate Tesseract and Indra OCR performance on a custom sample. The post A Developer’s Guide to OmniParseBench: Leaderboard Benchmarks and OCR Testing appeared first on MarkTechPost .
Exa 3.0 is a search API upgrade from Exa. It adds a larger embedding model, Exa Lite at $4 per 1,000 requests, and Dynamic Highlights, and leads 8 benchmarks Exa ran itself. The post Exa 3.0 Search API Tops Perplexity, Brave and Parallel on 8 Benchmarks appeared first on MarkTechPost .
