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Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units
Announce Type: replace Abstract: While Mechanistic Interpretability has identified interpretable circuits in LLMs, their causal origins in training data remain elusive. We introduce Mechanistic Data Attribution (MDA), a scalable framework that employs Influence Functions to trace interpretable units back to specific training samples. Through extensive experiments on the Pythia family, we causally validate that targeted intervention--removing or augmenting a small fraction of high-influence...
Integrated Evaluation of Osmotic and Antioxidant Defense Mechanisms in Cotton Genotypes Exposed to NaCl Stress
Salinity stress is one of the major abiotic factors limiting cotton productivity worldwide by inducing osmotic imbalance, oxidative stress, and metabolic disturbances in plant tissues. The present study aimed to evaluate the physiological and biochemical responses of different cotton (Gossypium hirsutum L.) genotypes under NaCl-induced salinity stress through analysis of proline accumulation, antioxidant enzyme activities, and lipid peroxidation intensity. The experiment was conducted under...
Modeling Depth Ambiguity: A Mixture-Density Representation for Flying-Point-Free Depth Estimation
Announce Type: new Abstract: Despite advances in depth estimation, flying points remain a persistent failure mode: near object boundaries, depth estimators often predict spurious 3D points in the empty space between foreground and background surfaces. We trace this artifact to a standard modeling choice: assigning each pixel a single depth hypothesis. At boundaries, a pixel can straddle a foreground and a background surface, so its true depth is ambiguous between the two.
Can You Stop a Hypersonic Missile?
Can You Stop a Hypersonic Missile? The headlines say yes. Patriot crews shot down a Kinzhal over Kyiv on the night of May 4, 2023.