research

Robustness of Constraint Automata for Description Logics with Concrete Domains

arXiv:2601.19644v2 Announce Type: replace-cross Abstract: Decidability or complexity issues about the consistency problem for description logics with concrete domains have already been analysed with t

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Sampling the Schwinger Model with Gauge-Equivariant Diffusion

DGX agent

arXiv:2606.27481v1 Announce Type: cross Abstract: We present a first study of a diffusion-based approach to accelerated sampling of the N_f = 2 lattice Schwinger model. Our work is inspired by recent

researcharxiv-cs-lg

29 Jun 2026

Scaling limit of the Random Language Model

arXiv:2606.28105v1 Announce Type: cross Abstract: We develop a quantitative theory of the Random Language Model (RLM), an ensemble of stochastic context-free grammars, in a scaling limit where the num

SEADA: An efficient methodology for optimizing mixed-precision DNNs on multi-precision spatial architectures

arXiv:2606.27884v1 Announce Type: cross Abstract: Mixed-precision computation has been introduced in deep neural networks (DNNs) as an effective approach to reduce latency, energy consumption, and mem

Second-Order KKT Guarantees for Bregman ADMM in Nonconvex and Non-Lipschitz Optimization

arXiv:2606.28307v1 Announce Type: cross Abstract: We analyze Bregman ADMM for nonconvex linearly constrained problems under two-sided relative smoothness, a condition that replaces the standard Lipsch

Self-Concordant Perturbations for Linear Bandits

arXiv:2510.24187v3 Announce Type: replace-cross Abstract: We consider the adversarial linear bandits setting and present a unified algorithmic framework that bridges Follow-the-Regularized-Leader (FTR

Self-Stigma Is Not a Monolith, but Generic Empathy Is: Persona-Conditioned LLM Support for People Who Use Drugs

arXiv:2606.23387v2 Announce Type: replace Abstract: Self-stigma predicts treatment avoidance and disengagement among people who use drugs (PWUD), yet conversational systems aiming to provide support t

SHIFT: Gate-Modulated Activation Steering for Knowledge Conflict Mitigation in Retrieval-Augmented Generation

arXiv:2606.27786v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) enhances LLMs by incorporating external knowledge to support response generation. However, conflicts between retr

SIGNER: Temporally Grounded Sign Language Generation via Time-Resolved Conditioning

arXiv:2506.07460v2 Announce Type: replace-cross Abstract: Sign language generation (SLG), also known as text-to-sign generation, aims to bridge the communication gap between signers and non-signers. U

Spectral Subsurface Scattering from RGB via Biophysical Skin Inversion

arXiv:2606.27604v1 Announce Type: cross Abstract: In this paper we present a spectral optical inversion for skin for path tracing-based rendering of subsurface scattering. Skin is a complex multilayer

SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes

arXiv:2508.12410v3 Announce Type: replace-cross Abstract: Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for red

StableMotion: One-Step Motion Estimation with Diffusion Prior

arXiv:2505.06668v2 Announce Type: replace Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion

STAG: Spatio-temporal Evolving Structural Representation of Action Units for Micro-expression Recognition

arXiv:2606.28083v1 Announce Type: cross Abstract: Micro-expression recognition is challenging due to subtle and short-lived facial muscle movements. Existing methods rely heavily on apex-onset frames,

starting today you can now see a breakdown of your context usage per session. smash that update button @NousResearch

Nous Research has released an update that allows users to view a detailed breakdown of their context token usage on a per-session basis. This feature enhancement enables users to better understand and

researchnous-research--x

Surprises in Proper Positive-Only Learning

arXiv:2606.28309v1 Announce Type: cross Abstract: Binary classification from positive-only samples is a variant of PAC learning in which the learner receives i.i.d. samples from the positive region of

Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits

arXiv:2602.09456v2 Announce Type: replace Abstract: We propose an algorithmic framework, Offline Estimation to Decisions (OE2D), that efficiently reduces contextual bandit learning with general reward

Tandem Reinforcement Learning with Verifiable Rewards

arXiv:2606.28166v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capability of large language models, reaching expert or e

Temporal Convolutional Autoencoder for Interference Mitigation in FMCW Radar Altimeters

arXiv:2505.22783v2 Announce Type: replace-cross Abstract: Reliable altitude estimation with frequency-modulated continuous wave (FMCW) radar altimeters is increasingly a challenge due to in-band inter

TeRoR: Decoupled Temporal Rotation with Relational Circular Region for Temporal Knowledge Graph Embedding

arXiv:2606.27651v1 Announce Type: new Abstract: In recent years, with the emergence of Temporal Knowledge Graphs (TKGs), research on learning entity and relation representations in TKGs has attracted

The Curse of Multiple Mediators: Hidden Interaction Effects in Activation Patching

arXiv:2606.27510v1 Announce Type: cross Abstract: Activation patching is the primary tool in mechanistic interpretability. It attributes causal responsibility for a model behavior to each of its indiv

The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails

arXiv:2606.27462v1 Announce Type: cross Abstract: The global minimum-variance portfolio (GMVP) is the canonical decision built from an estimated covariance matrix, yet covariance estimators are univer

The Download: metric weaknesses and AI elephant warnings

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The inevitable weakness of metrics There are plenty of useful

researchmit-tech-review

The Remittance Blueprint: Data-driven Intelligence for Sri Lanka

arXiv:2606.28190v1 Announce Type: cross Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data an

The Shift Toward Open and Reproducible AI Research

arXiv:2606.16974v3 Announce Type: replace Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices. Several studies have identified methodol

The Weakest Link Tells It All: Outcome-Supervised Process Reward Modeling via Learnable Credit Assignment

arXiv:2606.27739v1 Announce Type: new Abstract: Process reward models (PRMs) enhance the reasoning capabilities of large language models (LLMs) by providing fine-grained feedback, yet training PRMs ty

Toward Robust In-Context Segmentation via Concept Guidance

arXiv:2606.28149v1 Announce Type: cross Abstract: In-context segmentation (ICS) requires a model to segment target regions in a query image using only a few reference images and their corresponding ma

Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework

arXiv:2606.27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns rega

ToxiREX: A Dataset on Toxic REasoning in ConteXt

arXiv:2606.27981v1 Announce Type: new Abstract: We introduce a new, contextual, multilingual dataset called ToxiREX: Toxic REasoning in ConteXt. The dataset consists of threads of Reddit comments and

Training-free Uncertainty Guidance for Complex Visual Tasks with MLLMs

arXiv:2510.00705v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) often struggle with fine-grained perception, such as identifying small objects in high-resolution images or

Unbiased Diffusion Variational Inversion via Principled Posterior Matching

arXiv:2605.25042v2 Announce Type: replace Abstract: Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution a

Understanding How MLLMs Describe Artworks Using Token Activation Maps

arXiv:2606.27947v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When a

Unleashing Infinite Motion: Scaling Expressive Quadrupedal Motion via Generative Video Priors

arXiv:2606.28237v1 Announce Type: new Abstract: Quadruped robots have achieved remarkable locomotion, yet their behavioral repertoire remains confined to a few gaits--far from the expressive, companio

researcharxiv-cs-ro

USAD: Uncertainty-aware Statistical Adversarial Detection

arXiv:2606.27832v1 Announce Type: new Abstract: Statistical adversarial detection (SAD) treats detection as a two-sample test. Given a reference set of clean examples (CEs) and a batch of queries, pot

VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing

arXiv:2606.28301v1 Announce Type: new Abstract: Inference-time scaling is a promising paradigm to improve generative models, especially when outputs must satisfy structural constraints or optimize dow

Vision-Default, Prior-Override: Causal Mechanisms of Perception-Knowledge Conflict in Vision-Language Models

arXiv:2606.28273v1 Announce Type: new Abstract: Vision-language models must reconcile visual evidence with memorized world knowledge when the two conflict. How they resolve this conflict shapes the re

WattLayer: Get Layers Right to Estimate Inference Energy of Neural Networks

arXiv:2606.27841v1 Announce Type: cross Abstract: The widespread adoption of Artificial Intelligence (AI) has led to increasing concerns about energy consumption, yet there is a lack of standardized m

What Was That Again? Certified Robustness for Automatic Speech Recognition

arXiv:2606.27698v1 Announce Type: cross Abstract: Automatic Speech Recognition systems are notoriously both sensitive to adversarial and benign perturbations. While this has been repeatedly demonstrat

Which Nash Equilibrium? Solver-Dependent Selection on Zero-Sum Nash Polytopes

arXiv:2606.28308v1 Announce Type: cross Abstract: Many two-player zero-sum games admit not a unique Nash equilibrium but a convex set of them: a polytope of profiles that all share the minimax value V

It's quite rational to regulate frontier API models, especially to get more transparency for the government, without regulating open-source …

It's quite rational to regulate frontier API models, especially to get more transparency for the government, without regulating open-source AI. Here's why: 1. The most dangerous AI systems right now a

researchyann-lecun--x

Latest open artifacts (#22): Zyphra, Cohere, and Poolside are expanding the breadth of the ecosystem

This article discusses recent open-source AI model releases and developments from three companies—Zyphra, Cohere, and Poolside—and their contributions to expanding the broader AI ecosystem. It likely

researchinterconnects

New research from @nytimes finds that the US government is actively doing 'critical minerals' deals with FOURTEEN different companies that h…

New research from @nytimes finds that the US government is actively doing 'critical minerals' deals with FOURTEEN different companies that have financial ties to the Trump and/or Lutnick families - de

researchyann-lecun--x

Putin's cannon fodder: 'The average life expectancy of a new recruit—from arrival at a training ground to death in a combat zone—lies...betw…

Putin's cannon fodder: 'The average life expectancy of a new recruit—from arrival at a training ground to death in a combat zone—lies...between 10 days and 3 weeks. Once...sent onto the battlefield, R

researchyann-lecun--x

TechCrunch on Sakana Fugu and the broader conversation around frontier AI access in Asia. Our position remains that AI is best developed tog…

TechCrunch on Sakana Fugu and the broader conversation around frontier AI access in Asia. Our position remains that AI is best developed together rather than hoarded. Sakana AI will continue contribut

researchdavid-ha--x

To really move the needle in terms of innovation, like the era in Japan when you had companies like Sony or Panasonic come out, there are a …

To really move the needle in terms of innovation, like the era in Japan when you had companies like Sony or Panasonic come out, there are a few factors at play. One is that the nation needs to have a

researchdavid-ha--x

Come and take it

'Come and take it' is a historical phrase and motto associated with resistance to government authority, most famously used during the Texas Revolution (1835-1836) and later adopted in American politic

researchnous-research--x

Fugu-Ultra is now available on Vercel AI Gateway https://vercel.com/changelog/sakana-fugu-ultra-now-available-on-ai-gateway ✨

Sakana AI's Fugu-Ultra model is now available through Vercel's AI Gateway, expanding access to this language model through Vercel's infrastructure. This integration allows developers to use Fugu-Ultra

researchdavid-ha--x

Link to the full article: https://magazine.sebastianraschka.com/p/using-local-coding-agents

researchsebastian-raschka--x

This article explores the implementation and use of local coding agents—AI systems designed to autonomously write, test, and debug code on local machines without relying on external APIs. The piece li

Loop engineering is just prompt engineering with great system design.

Loop engineering refers to an iterative approach to AI system design that combines prompt engineering with robust system architecture, emphasizing that effective AI applications depend equally on how

researchdair-ai--x