Search: “framework”

Second Thought: Reasoning in Parallel as LLM Agents Act and Observe

arXiv:2608.13667v1 Announce Type: new Abstract: LLM agents in the ReAct paradigm alternate between reasoning, acting, and observing, but deliberate reasoning is confined to the Thought phase: while th

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Secret-Stego Dissimilarity as a Design Axis: Invertible Coverless Image Steganography with Diffusion Models

DGX agent

arXiv:2608.13597v1 Announce Type: cross Abstract: Coverless image steganography (CIS) synthesizes a stego image rather than modifying an existing cover image, enabling authorized recipients to reconst

researcharxiv-cs-ai

17 Aug 2026

SheetCompass: Hierarchical Relation Graphs for Agentic Spreadsheet Reasoning

arXiv:2608.14452v1 Announce Type: new Abstract: Spreadsheets are widely used to organize, analyze, and manipulate semi-structured data, yet automated spreadsheet reasoning remains challenging for larg

Smart routes: a system for development and comparison of algorithms for solving vehicle routing problems with realistic constraints

arXiv:2608.14140v1 Announce Type: new Abstract: The problem of route optimization with realistic constraints is becoming extremely relevant in the face of global urban population growth. While we are

Some thoughts on Dario’s post: 1. Dario does not actually address Gavin Baker’s account of what he said – something he could easily deny if …

Some thoughts on Dario’s post: 1. Dario does not actually address Gavin Baker’s account of what he said – something he could easily deny if it were inaccurate. 2. Dario claims his critics live in a “b

safetyyann-lecun--x

Spatial Message Passing in Language Space for Pathology Image Interpretation

arXiv:2608.14309v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) can generate pathological descriptions from histological images, but gigapixel Whole Slide Images (WSIs) exceed

local-aiarxiv-cs-cv

Tutorials

SPEAR: Structure Property Explainability with Attention Regularization

arXiv:2608.13826v1 Announce Type: cross Abstract: Machine learning is increasingly used to learn structure property relationships from spectroscopic and diffraction data, yet its adoption in materials

tutorialsarxiv-cs-lg

Split the Labor: Separating Evidence Interpretation from Decision Aggregation

arXiv:2608.14509v1 Announce Type: new Abstract: Systems that ask a language model to reach a conclusion from many sources usually concatenate them into one prompt. This conflates two operations with d

TENET: One Step Toward Test-Driven Development for Repository-Level Code Generation

arXiv:2509.24148v4 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation. With

The Metacognitive Bottleneck: Japanese Riddles Reveal Fundamental Limits of Machine Insight and Self-Evaluation in Reasoning AI

arXiv:2509.14704v3 Announce Type: replace Abstract: Benchmark saturation and training-data contamination increasingly obscure whether reported gains in large language models (LLMs) reflect genuine adv

Think in Latent, Explain in Language: Self-Explainable Latent Reasoning

arXiv:2608.13570v1 Announce Type: cross Abstract: Latent reasoning has emerged as a powerful alternative to text-based Chain-of-Thought (CoT), offering significant gains in computational efficiency by

Training-Free Knowledge Transfer Across Model Scales through Activation-Guided Pruning

arXiv:2608.13596v1 Announce Type: cross Abstract: Heterogeneous model fusion seeks to combine models that differ in tasks, initializations, architectures, or scales. We study an underexplored cross-sc

safetyarxiv-cs-ai

UMPIRE-Net: Unrolled Magnitude-Phase Regularization Network for Accelerated MRI

arXiv:2608.14422v1 Announce Type: cross Abstract: MRI reconstruction from undersampled k-space measurements is an ill-posed inverse problem. Physics-driven deep learning (PD-DL) methods have shown str

researcharxiv-cs-cv

Variation Brownian Kernel Ladders

arXiv:2608.13882v1 Announce Type: new Abstract: Claims about the benefit of depth depend on the complexity assigned to a representation. We introduce the Variation Brownian Kernel Ladder (VBKL), a pat

Where Does Vision Meet Language? Understanding and Refining Visual Fusion in MLLMs via Contrastive Attention

arXiv:2601.08151v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in vision-language understanding, yet how they internally integrate visua

researcharxiv-cs-cv

Why we need an AI-resilient society

arXiv:1912.08786v3 Announce Type: replace-cross Abstract: Three generations of software have transformed the role of artificial intelligence in society. In the first, programmers wrote explicit logic.

safetyarxiv-cs-ai

XSA-MAD: Cross-modal Semantic Alignment for Morphing Attack Detection

arXiv:2608.13861v1 Announce Type: new Abstract: Morphing attacks pose a serious threat to face recognition systems. However, existing image-based morphing attack detection (MAD) methods often generali

safetyarxiv-cs-cv

XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas

model-releasesarxiv-cs-cv

arXiv:2602.04819v5 Announce Type: replace Abstract: Accurate risk stratification of precancerous polyps during routine colonoscopy screening is a key strategy to reduce the incidence of colorectal can

Making small local models actually useful for coding

model-releasesr-localllama

Hey! Like a lot of people here with consumer GPUs (RTX 4060 8GB in my case), I wanted to see if I could use local models for daily coding tasks instead of burning cloud credits on simple boilerplate.

16 Aug 2026

2/2 Second, on the messaging around AI. I do not agree that my messaging has been disproportionately negative. In fact it has been about equ…

2/2 Second, on the messaging around AI. I do not agree that my messaging has been disproportionately negative. In fact it has been about equally balanced between risks and benefits: I’ve written one m

safetydario-amodei--x

15 Aug 2026

Sources: Mercor and other firms gathering data for AI labs are driving demand to buy or license internal datasets from startups shutting down or being acquired (Alix Coutures/The Information)

Alix Coutures / The Information: Sources: Mercor and other firms gathering data for AI labs are driving demand to buy or license internal datasets from startups shutting down or being acquired — Eight

agentstechmeme

15 Aug 2026

A Hierarchical Energy-Based Model for Multimodal Cognition

arXiv:2608.12398v1 Announce Type: cross Abstract: We propose IM-LEPP (Integrated Multimodal Latent Energy-based Predictive Processing), a hierarchical, energy-based model of multimodal cognition that

A Lyapunov Drift-Plus-Penalty Method Tailored for Reinforcement Learning with Queue Stability

arXiv:2506.04291v2 Announce Type: replace Abstract: With the proliferation of Internet of Things (IoT) devices, the demand for addressing complex optimization challenges has intensified. The Lyapunov

A modest community proposal for desloppification

Over & over I see people post slop and excusing it as 'english is not my native language'. As if, if we could understand their language we'd see they wrote it all by hand Fine then, new rule: > if you

local-air-localllama

a very modular harness 👌

model-releasesyohei-nakajima--x

a very modular harness 👌 🧩 DeepSeek Harness v0.1 is now available in Developer Preview! 🔹 We’re opening it up to developers building agent harnesses worldwide and open-sourcing the codebase in MIT lic

Accelerated Markov Chain Monte Carlo Algorithms on Discrete States

arXiv:2505.12599v3 Announce Type: replace-cross Abstract: We propose a class of discrete state sampling algorithms based on Nesterov's accelerated gradient method, which extends the classical Metropol

AmalthAI: An Open-Source Computer Vision Platform for Cultural Heritage

arXiv:2608.13343v1 Announce Type: new Abstract: Computer vision (CV) and machine learning (ML) offer new tools for cultural heritage (CH) artifact analysis, but the CV/ML pipeline remains largely inac

local-aiarxiv-cs-cv

arepsilon-MemEvo: Adaptive Cross-Task Memory Transfer for LLM Program Evolution

arXiv:2608.12522v1 Announce Type: new Abstract: LLM-based program evolution systems such as FunSearch and AlphaEvolve have shown strong ability to discover novel algorithms, but typically optimize eac

ASPIRE-VINS: Adaptive Spline-based Visual-inertial Navigation System With Robust 3D Measurement Residuals

arXiv:2608.12840v1 Announce Type: new Abstract: Visual-inertial navigation systems estimate six-degree-of-freedom motion by fusing visual and inertial data. Modern discrete-time methods with IMU prein

researcharxiv-cs-ro

Hardware

Balanced Adaptive Prototype Selection for Scalable TabPFN Inference on Large-Scale Tabular Data

arXiv:2608.12989v1 Announce Type: new Abstract: Pretrained tabular foundation models have demonstrated strong predictive capability; however, their application to large-scale datasets remains constrai

hardwarearxiv-cs-lg

Beyond Correctness: Benchmarking and Aligning Response Behaviors in Hybrid-Thinking MLLMs

model-releasesarxiv-cs-cv

arXiv:2608.12781v1 Announce Type: new Abstract: Hybrid-thinking multimodal large language models (MLLMs) allow a single model to alternate between deliberative thinking and latency-efficient non-think

Beyond Final Scores: A Systematic Evaluation of Agents for Long-Horizon AI Research and Development

arXiv:2608.13417v1 Announce Type: new Abstract: Autonomous agents are increasingly capable of improving models, systems, and other technical artifacts through long-horizon experimentation. To understa

Applications

Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcity

arXiv:2608.13197v1 Announce Type: new Abstract: Falls are a major health concern for older adults, and wearable sensors have been widely explored for detecting falls and enabling timely intervention.

applicationsarxiv-cs-lg

Beyond Visual Evidence: Revealing and Mitigating Relational Privacy Leakage in Document MLLMs

model-releasesarxiv-cs-cv

arXiv:2608.12911v1 Announce Type: new Abstract: While the privacy risks of multimodal large language models (MLLMs) have drawn significant attention, the unique vulnerabilities of domain-specific MLLM

Black-Box Knowledge Transfer across Distinct Feature Sets

arXiv:2608.12403v1 Announce Type: cross Abstract: Pre-trained black-box predictive functions encode knowledge distilled from massive datasets and extensive computation. However, when the available inp

BoardroomAI: Dependency-Aware Human-Steerable Multi-Agent Deliberation through Evolving Decision Graphs

arXiv:2608.13046v1 Announce Type: new Abstract: Organizational decisions are co-created while evidence, constraints, and human priorities continue to evolve. In conventional transcript-based multi-age

BrainWAM: Action-Space Coordination of Semantic Priors and Predictive Dynamics for Autonomous Driving

arXiv:2608.12854v1 Announce Type: cross Abstract: Autonomous driving requires planning under both semantic constraints and predictive dynamics. Existing end-to-end driving approaches, however, typical

Chance-constrained selection of sequential intervention strategies from counterfactual estimates

arXiv:2608.13209v1 Announce Type: cross Abstract: Many operational decisions are sequences of interventions under a cumulative resource limit, such as a maintenance schedule within a crew-hour budget.

safetyarxiv-cs-lg

CityRiSE: Reasoning Urban Socio-Economic Status in Large Vision-Language Models via Reinforcement Learning

arXiv:2510.22282v2 Announce Type: replace-cross Abstract: Urban socio-economic sensing plays a vital role in advancing global sustainable development goals. With the advent of Large Vision-Language Mo

Tutorials

Class Geometry as Supervision for Sample-Efficient Open-World Detection

arXiv:2608.12698v1 Announce Type: new Abstract: Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is esp

tutorialsarxiv-cs-cv

CoMedBench: A Multi-Source Benchmark of Synthetic Medical Data Fidelity and Downstream Utility

model-releasesarxiv-cs-lg

arXiv:2608.12805v1 Announce Type: new Abstract: Access to clinical data is essential for developing reliable healthcare machine learning systems, but direct use of electronic health records is constra

Comparative Analysis of Multilingual Pre-trained Models for Nepali Automatic Speech Recognition

arXiv:2608.12327v1 Announce Type: cross Abstract: Multilingual pretrained models nominally support Nepali, yet no controlled benchmark has compared them under a single fine-tuning protocol. We fine-tu

Confidence-Calibrating Regularization for Robust Brain MRI Segmentation Under Domain Shift

arXiv:2509.23176v2 Announce Type: replace Abstract: The Segment Anything Model (SAM) exhibits strong zero-shot performance on natural images but suffers from domain shift and overconfidence when appli

researcharxiv-cs-cv

Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation

arXiv:2608.13391v1 Announce Type: new Abstract: Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation b

safetyarxiv-cs-cv

CoverPrune: Coverage-Driven Token Pruning for 3D VLMs via Optimal Transport

arXiv:2608.13226v1 Announce Type: cross Abstract: While 3D Vision-Language Models (3D VLMs) have demonstrated remarkable spatial reasoning capabilities, they suffer from massive visual token counts th

DAPD: Dual-Anchored Policy Distillation

arXiv:2608.01735v2 Announce Type: replace Abstract: On-policy (self) distillation (OPSD) is increasingly adopted for language-model post-training. It strengthens the teacher with privileged informatio

safetyarxiv-cs-ai

DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

arXiv:2608.12980v1 Announce Type: new Abstract: Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Exist

local-aiarxiv-cs-cv

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming

arXiv:2608.12757v1 Announce Type: cross Abstract: Laplacian-regularized minimization is fundamental in signal processing and machine learning, but is limited by the dense and ill-conditioned nature of