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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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3 results for “DoRA”

Scaling DoRA: High-Rank Adaptation via Factored Norms and Fused Kernelscs.LG

DoRA improves adaptation efficiency for large models by factoring norms and fusing kernels.

problem High-rank DoRA is computationally expensive and infeasible on common GPUs.

method Factored norms and fused Triton kernels to reduce memory and speed up computation.

result Fused implementation is up to 2.0x faster for inference and 1.9x faster for gradient computation.

DoRA weight-decomposition factored norms fused kernels vision-language models

2026-03-23abs ↗pdf ↗

DORA: Exploring Outlier Representations in Deep Neural Networkscs.LG

DORA analyzes deep neural networks' internal representations to detect spurious correlations.

problem Detecting spurious correlations in deep neural networks' internal representations.

method DORA uses Extreme-Activation (EA) distance measure to assess representation similarities.

result Identifies internal representations capable of detecting spurious correlations.

Deep Neural Networks Representation Analysis Spurious Correlations Extreme-Activation Artifacts

2022-06-09abs ↗pdf ↗

DORA The Explorer: Directed Outreaching Reinforcement Action-Selectioncs.LG

Exploration is a fundamental aspect of Reinforcement Learning, typically implemented using stochastic action-selection. Exploration, however, can be more efficient if directed toward gaining new world knowledge. Visit-counters have been proven useful both in practice and in theory for directed exploration. However, a m…

2018-04-11abs ↗pdf ↗