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CS336: Language Modeling from Scratch
Course Staff Logistics - Lectures: Monday/Wednesday 3:00-4:20pm in Skilling Auditorium - Recordings: YouTube playlist - Office hours: - Percy Liang: Fridays 11am-12pm in Gates 366 - Tatsu Hashimoto: Tuesdays 11-12am in Gates 364 - Marcel Rød: Tuesdays 4:30-5:30pm in Gates 498, Wednesdays 4:30-5:30pm in Gates 415 - Herman Brunborg: Wednesdays 1:30-2:30pm, Fridays 1:30-2:30pm, location Gates 392 - Steven Cao: Mondays 4:30-5:30pm, Thursdays 9:30-10:30am, Gates 200 - Contact: Students should ask...
Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails
arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesirable outputs during deployment. In this paper, we examine how these filtering and moderation decisions produce forms of epistemic erasure and reveal tensions both across automated systems and between these systems and human judgment. We audit four pretraining filters and three inference-time...
IndoBias: A Dual Track Culturally Grounded Benchmark for LLMs Bias Evaluation in Indonesian Languages
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WAON: A Large-Scale Japanese Image-Text Dataset for Cultural Adaptation in Contrastive Vision-Language Models
arXiv:2510.22276v3 Announce Type: replace Abstract: Contrastive vision-language models have achieved remarkable progress through large-scale pretraining. Recent work has shown that removing English-only caption filters and pretraining on global data is effective for improving multicultural performance. We study whether such global pretraining is sufficient for culture-specific understanding, or whether further adaptation with natively sourced data can boost performance beyond what global...
FOLD: Fuzzy Online Deduplication for Very Large Evolving Datasets via Approximate Nearest Neighbor Search
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MiNI-Q: A Miniature, Wire-Free Quadruped with Unbounded, Independently Actuated Leg Joints
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Human-Like Neural Nets by Catapulting
Human-like Neural Nets by Catapulting Speculative proposal to create artificial neural nets with human-like performance by high-learning-rate/regularization training of overparameterized NNs to trigger catapulting/grokking. Over-parameterization as a route to true generalization would resolve many outstanding mysteries of artificial versus natural intelligence. There are many mysteries about deep learning and human intelligence, but we could describe the biggest anomaly this way: why are...
Book Dedications
To my sister, Dr. Soma Mohammed Mohammed Baroud. I write your name in full, because that is how it appeared on the white body bag that held your remains soon after the bomb was dropped. Dedications A random assortment of book dedications.
The secret underground system keeping the Grand Canyon alive
The secret underground system keeping the Grand Canyon alive - Date: - June 2, 2026 - Source: - Northern Arizona University - Summary: - Scientists are venturing into the Grand Canyon’s hidden cave networks to solve a mystery: how snowmelt travels underground to supply the park’s vital springs. Their discoveries could help protect the canyon’s water from drought, contamination, and other growing threats. - Share: Every year, millions of people visiting Grand Canyon National Park stop at one...