The Archive

Comprehensive study of learned image compression design choices balancing perceptual quality and runtime, introducing novel techniques for practical human-visual-system-optimized codecs.

Case study of high-school/undergraduate students using AI tools for financial forecasting research, highlighting human-AI co-mentorship acceleration of learning outcomes.

Coding agent with executable Python world models, verification, and simplicity-bias refactoring solves 25 public ARC-AGI-3 games without task-specific logic.

Koopman operator theory applied to LLM embeddings as dynamical system enables low-cost black-box hallucination detection without sampling or external retrieval.

T-LVMOGP framework scales Multi-Output Gaussian Processes to high-dimensional outputs via transformed latent variables.

Anthropic secures partnership with SpaceX for 300MW+ compute at Colossus 1, adding 220k+ NVIDIA GPUs within one month.

Partnership with spaceX, anthropic just doubled the limits, source: https://x.ai/news/anthropic-compute-partnership

Move comes as CCP Games spends $120M to go independent, rebrands as Fenris Creations.

CausalFlow-T applies DAG-constrained normalizing flows and LLM-driven imputation for treatment effect estimation in incomplete EHR data.

Data-driven anomaly detection flags unusual patient-management actions in EHR systems to reduce clinical errors.

Adaptive policy selection method improves offline-to-online RL by combining off-policy and online evaluation under interaction budgets.

Multi-view evidential reasoning framework for mental health prediction from text with calibrated uncertainty estimation.

SHAP-based feature selection and hybrid boosting classify driving behaviors from multimodal physiological signals (EEG, EMG, GSR).

Wasserstein Gradient Flow analysis characterizes Generative Modeling via Drifting (GMD) as fixed-point optimization in probability measure space.

Analysis of LLM jailbreak vulnerability without structured prompts reveals robustness gaps in current safety defenses.

Manifold steering interventions causally link neural activation geometry to model behavior via structured representation space.

Finite-width signal propagation analysis shows when infinite-width approximation breaks down in long linear recurrences.

Proposes Prefix Sampling to optimize RL training efficiency by maintaining 50% pass rate—the regime maximizing reward signal and entropy in agentic tasks like SWE-bench.

LineRides framework enables bicycle robot to learn complex stunts via line-guided RL without demonstrations, using spatial guidelines and sparse keyframe constraints.

Framework for materials science dataset construction balancing targeted property optimization against preservation of untargeted outcomes via diversity-aware selection.

Introduces Concept Field method to detect hallucination and measure novelty in LLM outputs by modeling semantic drift in text corpora using sentence embeddings.

Unified theoretical framework for distributional regret bounds in bandits and episodic RL, with UCBVI-style algorithm achieving gap-independent guarantees.

Anthropic partners with SpaceX for compute capacity; removes Claude Code peak-hour limits and raises API rate limits for Opus.

Analysis of 100 most popular hardware configurations for local LLM inference on Hugging Face reveals deployment patterns and infrastructure preferences.

Memini: associative memory system with multi-timescale dynamics for continual knowledge updating in deployed LLMs without explicit management.

Bayesian framework for active view selection in 3D reconstruction using posterior inference over implicit surfaces.

Doubly sparse regularization exploiting Gaussian graphical model structure for high-dimensional regression.

Announced in the code w/claude programme. Hope to see claude back on top especially with the new rate limits!

Driver-WM: latent world model for predicting driver reactions during L2/L3 automation transitions using in-cabin behavioral dynamics.

Think-aloud traces improve automated cognitive model discovery beyond behavior-only constraints in risky decision-making tasks.