The Archive

Formal explainability method identifying destructive minimal supports as abductive explanations for tournament rule outcomes across six voting mechanisms.

BasketballBench: multimodal benchmark with 7,980 QA pairs across ten tasks (events, localization, player ID, game knowledge) from 2025-26 NBA season.

ChebBooster: training-free Chebyshev polynomial extrapolation for stable diffusion transformer inference acceleration without costly cache reuse schemes.

CNN-based transit detection pipeline for long-period exoplanets (>342 days) in Kepler field, addressing observational bias toward shorter orbital periods.

Bibliometric analysis of 7,120 Arabic NLP papers (1960–2026) identifies research trends, topic evolution, and gaps via BERTopic and social network analysis.

Empirical study formalizes and evaluates IR model robustness when non-relevant documents are added to collections, testing BM25 and listwise rerankers.

SkillAlchemy enables language agents to autonomously create reusable skills from open-world materials without human authorship or execution traces.

Formalizes quantitative trading via latent state mechanisms and five canonical constants; not directly relevant to AI systems or frontier models.

STONIC measures LLM value consistency across questionnaire ratings, pairwise choices, and generated text on 5,144 scenarios across four banks.

Next-scale transformer enables photorealistic multi-view human face synthesis at high resolution without 2D pre-training; narrow multimodal application.

Discrete Diffusion Models for recommendation systems enhanced with noise rescheduling to integrate item-based collaborative filtering.

MediSkill-Evo evolves clinical agent process knowledge across skill, rule, schema, and measurement banks with constraint-governed self-improvement.

Controlled pilot compares LLM-agent decomposition strategies (one wide vs. five narrow agents) on cross-border VAT determination with oracle labels.

KellyBoost applies XGBoost with Kelly criterion loss for growth-optimal portfolio allocation; financial ML application, not core AI infrastructure.

Proposes scaling law for tokenization in billion-scale user representation learning, addressing diminishing returns from raw data.

Studies cross-domain data-to-text generation without in-domain training, comparing LLM zero-shot vs. knowledge-driven approaches.

Introduces CLAW-4L benchmark for cross-lingual biography enrichment using claim extraction from non-English Wikipedia editions.

Derives theoretical bounds on reconstruction attacks against privacy-preserving instance encoding via spectral analysis.

General Intuition, the startup building a foundation model that trains generalized AI agents how to move through space and time, is in talks to raise at a $6 billion pre-money valuation from new investors including Valor Ventures, Point72 Ventures, Seven Seven Six.

Demonstrates adversarial attacks on Gumbel-based LLM weight exfiltration detection by manipulating prompt entropy distributions.

Proposes Dual-Stream Attention framework for 12-week influenza forecasting by conditioning numeric epidemiological and textual signals.

Analyzes how LLMs fail at tracking logical exclusions and proposes Logic-Augmented Generation with POLANYI++ for structured output.

Proposes DF-MoE sparse mixture-of-experts architecture combining 8+ audio-visual feature extractors for generalizable deepfake detection.

The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs,... The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs, the scale-out network connecting these nodes has emerged as a first-order performance bottleneck. For decades, traditional off-the-shelf Ethernet has been the undisputed king of enterprise and cloud networking. It is cheap, standardized… Source

Characterizes low-resource language underperformance in LLMs via representational geometry, finding degeneration in final layers.

Proposes Hierarchical Exponential-Gaussian Mixture model addressing variance collapse in watch-time distribution prediction for video recommendation.

AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing... AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing context from one turn to the next. The scale of this shift is now visible in raw consumption: across 100 trillion tokens of real-world usage, OpenRouter’s State of AI report found that average prompt tokens per request grew roughly fourfold… Source

Traditional cloud infrastructure was designed for predictable, general-purpose workloads and standard interfaces. Agentic AI factories connect diverse users,... Traditional cloud infrastructure was designed for predictable, general-purpose workloads and standard interfaces. Agentic AI factories connect diverse users, agents, applications, data sources, and storage systems to massively accelerated compute at multi-terabit bandwidth per server, making dedicated DPU processing essential for line-rate networking, storage, and security. Source

AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks.... AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks. While GPUs run the models, CPUs handle orchestration, tool execution, and sandboxed computation. Unlike conventional computing with stable runtime profiles, agentic workloads are unpredictable and highly variable. Based on telemetry from… Source

NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform. At the core of the platform is NVIDIA Vera Rubin NVL72, the... NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform. At the core of the platform is NVIDIA Vera Rubin NVL72, the most versatile machine ever built, delivering high throughput and interactivity across the widest range of AI workloads—from small to large models, both open and closed. Groq 3 LPX, when paired with Vera Rubin NVL72, extends the platform’s… Source