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Formula-Driven Supervised Learning (FDSL) enables vision pre-training without real images, but existing methods cast ...
We present EasyProver, a Lean proving system built from recursive agents with isolated contexts, asynchronous search,...
Whether models trained on different modalities converge to the same representation of the world is central to AI. The...
Blockchain forensics is adversarial and open-ended: money launderers split, swap, and bridge funds, cut their trail a...
Foundation models are typically trained in stages: pretraining, midtraining, supervised fine-tuning (SFT), and reinfo...
Developers download quantized large language models (LLMs) from public registries to run them locally. None of the re...
Language agents increasingly act through external tools and interactive environments, making the interface between th...
Autoregressive (AR) image generators are powerful in principle but inflexible in practice: training with a fixed rast...
Self-distillation offers a way to improve reasoning models when a suitable external teacher is unavailable. However, ...
Quarterly earnings forecasting requires an agent to connect financial evidence to the income-statement line items tha...
Clinical genomic analysis requires experts to integrate evolving guidelines, databases, and computational evidence. A...
Automated computational science could accelerate discovery by selecting, adapting and developing numerical methods. T...