Boltzmann MapReduce: A Partition-Function Reduce for Forkable Sandboxes
arXiv:2607.09689v1 Announce Type: new
Abstract: To leading order under local asymptotic normality (LAN), the confidence density a worker emits over a chunk of size $n$ is a Gibbs--Boltzmann measure $\exp\{-\beta E(\theta)\}$ whose inverse temperature is the sample size, $\beta=n$. Three consequence...
Interpreting Latent CoT Reasoning as Dynamical Systems
arXiv:2607.09698v1 Announce Type: new
Abstract: Recent latent reasoning methods, such as CODI and COCONUT, face a fundamental interpretability problem: they maintain multiple superimposed candidate traces in the hidden space at each step, unlike explicit- CoT, which follows a single transparent rea...
Multilingual Semantic Retrieval for Apple Music Search
Apple Music serves listeners across 150+ storefronts in dozens of languages, with a catalog that grows by hundreds of thousands of new tracks daily. At this scale, search recall on misspelled, transliterated, and cross-lingual queries becomes a dominant driver of session quality, particularly for ta...
Verifying Rust cryptography in SymCrypt, from standards to code
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves.
The post Verifying Rust cryptography in SymCrypt, from standards to code appeared fir...
Reward Transport: Property Control in Flow Matching via Noise-Space Alignment
arXiv:2607.08781v1 Announce Type: new
Abstract: The coupling in flow matching -- the rule pairing noise vectors with data points -- is typically treated as a computational choice. We show that this coupling can instead serve as an alignment interface: by matching noise and data according to a targe...
Signed Symmetric Quantization for Few-Bit Integers
arXiv:2607.08779v1 Announce Type: new
Abstract: The signed integer alphabet contains one more negative representable value than positive. Yet, by convention, the standard symmetric integer quantizer fixes its scale to be strictly positive, which assigns this extra representable value to the negativ...
iLENS: Interpretable LLM-Guided Mixture-of-Experts for Neuroimaging Survival Analysis
arXiv:2607.08778v1 Announce Type: new
Abstract: Alzheimer's Disease (AD) is a complex neurodegenerative disorder that continues to impact millions of people worldwide. Predicting AD conversion during the prodromal stage remains critical for disease understanding and patient care. As such, survival ...
Stanford Study Exposes Major Flaw in AI Mental Health Safety Testing
With increased use of chatbots in mental health contexts, AI developers now rely on human experts to evaluate AI’s responses for “safety” – but experts rarely agree on what’s safe.
LLT: Local Linear Transformer for PDE Operator Learning
arXiv:2607.07718v1 Announce Type: new
Abstract: Neural operators have become a common approach for learning PDE solution maps and accelerating numerical simulations. Transformer-based neural operators are of particular interest, since attention can learn long-range dependencies in the computational...
Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification
arXiv:2607.07717v1 Announce Type: new
Abstract: In chest X-ray (CXR) classification, acceptable ranking performance can still leave rare-positive patients below threshold, especially within subgroups. We study this pre-deployment fairness problem as an audit question: after a long-tailed multi-labe...
New York's AI scene: The 25 companies you need to know
New York's AI companies are embedding AI into industries the city already runs: trading floors, hospital records, compliance desks. This list of 25 names, from Hugging Face to Dataminr, maps what that looks like in practice, and why the city's AI economy no longer needs Silicon Valley's permission.
AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation
arXiv:2607.06624v1 Announce Type: new
Abstract: We present AgentLens, a production-assessed benchmark for interactive code agents. Most code-agent benchmarks reduce a run to a single bit -- did the task pass? -- but the people who actually use these agents experience the entire trajectory: how the ...
Deep Reinforcement Learning for Reliability Based Bi-Objective Portfolio Optimization
arXiv:2607.06610v1 Announce Type: new
Abstract: Portfolio optimization under uncertainty is inherently a multi-objective decision problem involving complex interactions among return, risk, market dynamics, and practical investment constraints. Existing reliability based portfolio optimization appro...
NEST: Tackling Dataset-Level Distribution Shifts via Regime-Oriented Mixture-of-Experts
arXiv:2607.06607v1 Announce Type: new
Abstract: Accurate long-term forecasting in complex systems is frequently compromised by dataset-level distribution shifts, where diverse underlying behavioral modes and evolving system states drive the dynamic multivariate time-series. While existing methods p...
Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why
On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this signal is beneficial and under which it is detrimental. Which teacher model should be used, and in the case of self-distillation, which specific context s...
From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond
arXiv:2607.05563v1 Announce Type: new
Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of why a system behaves in a certain way under different inputs. Unlike traditional explainability met...
The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error
arXiv:2607.05450v1 Announce Type: new
Abstract: This paper explores the "Granularity Paradox" in time-series forecasting, wherein finer temporal disaggregation (e.g., Monthly to Weekly/Daily) improves in-sample diagnostics and dataset size (N), but degrades out-of-sample accuracy due to recursive e...
Geometry-Aware Infrastructure-Anchored Denoiser for UWB Sensing and Work-Zone Reconstruction
arXiv:2607.05449v1 Announce Type: new
Abstract: Accurate work-zone geometry perception is critical for intelligent transportation systems, and ultra-wideband sensing offers a low-cost approach for infrastructure-aided reconstruction. However, outdoor UWB ranging is often degraded by non-line-of-sig...
arXiv:2607.02542v1 Announce Type: new
Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actions over extended horizons. Existing approaches typically specialize in visual-language reasoning, v...
Sparse Mixture-of-Experts (MoE) architectures route each token through a subset of experts at each layer independently. We propose viewing MoE computation through the lens of expert paths—the sequence of expert selections a token makes across all layers. This perspective reveals that, despite N^L po...
Quantum mechanics once baffled scientists. Now it's changing the world
Quantum mechanics has journeyed from a strange and controversial idea to the foundation of some of humanity’s most advanced technologies. Now researchers are pushing its boundaries even further, with potential breakthroughs in energy, medicine, computing, and our understanding of the universe.