All entries

RSI is not happening [R]

model-releasesr-machinelearning

A new paper (I'm not a coauthor BTW -- I just found it interesting) argues, basically, that RSI1 is not on the horizon2, because current (at the time the study was done) agents cannot do open-ended ML

Running Qwen 3.8 next on 16vram+32ram - A useful/fun post for the gpu poors

Content type

All Blog X Post Paper YouTube Reddit GitHub

Hello Reddit. Posting this for fun. I thought it was a lonely and silly journey to set up Qwen 3.8 Next on a system that doesn't really run it properly—it was a challenge that might help the community

model-releasesr-localllama

14 Sept 2026

Running Qwen3.8-Flash-Next locally on a 12GB VRAM card

model-releasesr-localllama

Now that the dust has settled a bit - here's a write-up on running Qwen3.8-Flash-Next (125B-A6B MoE + 51B n-gram table) on relatively middle-tier hardware (RTX 4070 12GB + 64GB DDR5-5600 + Gen4 NVMe o

RunningTensor: Generalizing Linear Attention to Higher-Order Recurrent States

arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi

Tutorials

SAGE-Loop: Reliable Closed-Loop LLM-Driven AutoML with Trial-and-Correction and Adaptive Ensembling

arXiv:2609.12455v1 Announce Type: new Abstract: Automated machine learning (AutoML) is reshaping data-driven science and industrial practice, and as large language models are introduced into AutoML, p

tutorialsarxiv-cs-lg

Industry

Sam Altman and Elon Musk back Dario Amodei’s call to slow down the frontier of AI development

Anthropic PBC Chief Executive Dario Amodei has once again called for the artificial intelligence industry to slow down the pace of frontier model development, only this time he’s being backed by two b

industrysiliconangle

Same Encoder, Different Winner: A Paired-View Framework for Cell Painting Encoder Evaluation

arXiv:2609.12761v1 Announce Type: new Abstract: Vision encoders for Cell Painting are typically ranked by a single evaluation, commonly replicate mean average precision (mAP). We introduce CP-BG-Bench

Sampling via Decision-Flow: Training-Free Extraction of Improved Latent Reasoning Paths in Large Language Models

arXiv:2609.12317v1 Announce Type: new Abstract: A central question in LLM reasoning is whether reinforcement learning (RL) instills genuinely new capabilities or merely reshapes how existing knowledge

Agents

SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking

arXiv:2609.13141v1 Announce Type: new Abstract: Post-training attention sparsification reduces the quadratic cumulative attention cost of pretrained Transformers by selecting a small set of context un

agentsarxiv-cs-cl

Satisficing Regret Minimization in Bandits: Constant Rate and Light-Tailed Distribution

arXiv:2406.06802v4 Announce Type: replace-cross Abstract: Motivated by the concept of satisficing in decision-making, we consider the problem of satisficing regret minimization in bandit optimization.

applicationsarxiv-cs-lg

Scalable Discrete-to-Continuous Channel Simulation for Compression and Privacy

arXiv:2609.12067v1 Announce Type: new Abstract: Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are t

Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning

arXiv:2502.07250v3 Announce Type: replace Abstract: Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many

Tutorials

SCDM: Spatial-Contextual Disentanglement Mamba via Differential Inference for Efficient Image Classification

arXiv:2609.12825v1 Announce Type: new Abstract: State Space Models (SSMs), particularly VMamba, have emerged as efficient alternatives for modeling long-range dependencies in medical image analysis. H

tutorialsarxiv-cs-cv

Scenario-Independent Criticality Assessment and Prediction for Vulnerable Road Users in Autonomous Driving

arXiv:2609.11947v1 Announce Type: cross Abstract: Increasing safety is the primary objective of automated vehicles. Achieving this goal requires reliable safety metrics that incorporate safety-relevan

safetyarxiv-cs-cv

SCOPE-OPSD: Fisher-Conditioned Privileged Subspaces for On-Policy Self-Distillation

arXiv:2609.12579v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) scores student-generated prefixes with a solution-conditioned self-teacher, yet transfers supervision only through ne

safetyarxiv-cs-lg

Score-based Outlier Generation via Controlling the Radon-Nikodym Derivative

arXiv:2609.12113v1 Announce Type: new Abstract: Outliers are important for stress-testing algorithms and understanding system behaviour under rare conditions. Despite being commonly described as low-l

SCORE: SubDistribution-aware Collaborative Knowledge Reinforcing for Cloth-Hybrid Lifelong Person Re-Identification

arXiv:2609.12577v1 Announce Type: new Abstract: Lifelong Person Re-Identification (LReID) aims to train a unified person retrieval model from a non-stationary data stream. Existing LReID methods mainl

Self-supervised Pre-training Helps Retinal Disease Progression Modelling Most When Data Is Scarce

arXiv:2609.12834v1 Announce Type: new Abstract: Modelling how a disease progresses over time requires longitudinal imaging cohorts, which are scarce and small, whereas cross-sectional data -- one imag

Self-Verifying Anomaly Detection using Explainable AI for Cybersecurity of DER Networks

arXiv:2609.12305v1 Announce Type: cross Abstract: The rapid growth of Distributed Energy Resources (DERs) has significantly expanded the cyber attack surface of modern power grids. Furthermore, increa

Semantically Aligned Gradient-Driven Context-Preserving Image Editing

model-releasesarxiv-cs-cv

arXiv:2609.12691v1 Announce Type: new Abstract: Instruction-guided image editing has a training-time blind spot. Generative editors are never required to semantically verify whether their outputs actu

short summary of GPT-6 Astra and why it doesn’t bail OpenAI out of its economic mess:

short summary of GPT-6 Astra and why it doesn’t bail OpenAI out of its economic mess: they have made lots of progress (partly using neurosymbolic techniques!) on problems that can be formally verified

safetygary-marcus--x

SIFPBPNet: A Dual-Path Network for Wearable and Cuffless Blood Pressure Estimation via Individualized Steady-state Representation

arXiv:2609.12690v1 Announce Type: new Abstract: Continuous and cuffless blood pressure (BP) monitoring using photoplethysmography (PPG) is of great interest for low-cost and personalized cardiovascula

Simplifying ROS2 controllers with a modular architecture for robot-agnostic reference generation

arXiv:2601.08514v3 Announce Type: replace Abstract: This paper introduces a novel modular architecture for ROS2 that decouples the logic required to acquire, validate, and interpolate references from

researcharxiv-cs-ro

SIMS: Scale-Invariant Merit-Function-Based Scalarization for Multi-Task Learning

arXiv:2609.12599v1 Announce Type: new Abstract: Multi-task learning (MTL) requires navigating unavoidable trade-offs among competing objectives. This paradigm is frequently formulated as multi-objecti

Simulating Disengaged Students to Evaluate LLM-based Tutors

arXiv:2609.12331v1 Announce Type: new Abstract: Simulated students generated by computational models provide a practical way to evaluate tutoring strategies and pedagogical approaches used by human an

Single-Query Person-Centric Bimanual Hand-Object Interaction Detection

arXiv:2609.12155v1 Announce Type: new Abstract: Understanding person-level bi-manual interactions requires not only detecting hands, but also identifying which two hands belong to the same person and

Size Doesn't Matter: Material-State Reinforcement Learning for Excavator Transferable Soil Manipulation

arXiv:2609.12677v1 Announce Type: new Abstract: Earthmoving tasks such as excavation, backfilling, or embankment construction require deliberate repositioning of deformable soil. For these tasks, huma

safetyarxiv-cs-ro

SNAP3D: Physically Grounded 3D Parts for Assembly from a Single Image

arXiv:2609.13146v1 Announce Type: cross Abstract: Part-aware 3D asset generation enables applications such as editing, articulation, simulation, and fabrication, yet existing methods can generate visu

applicationsarxiv-cs-cv

Industry

Sources: OpenAI bought Glass Imaging, which is developing AI-powered smartphone camera tech, in a deal valuing it at 300M+; it was valued at ~100M last year (Wall Street Journal)

Wall Street Journal: Sources: OpenAI bought Glass Imaging, which is developing AI-powered smartphone camera tech, in a deal valuing it at 300M+; it was valued at ~100M last year — Glass Imaging, value

industrytechmeme

Industry

Sources: Trump met privately with Sam Altman backstage at the GOP midterm convention, where they discussed AI and its growing power, at Altman's request (MS NOW)

MS NOW: Sources: Trump met privately with Sam Altman backstage at the GOP midterm convention, where they discussed AI and its growing power, at Altman's request — Altman, Elon Musk and Anthropic chief

industrytechmeme

Local Ai

Space as an Interventional Invariant: Cross-Modal Predictive Geometry for Stratified Cities and Em-Spaced Intelligence

arXiv:2609.11959v1 Announce Type: cross Abstract: Space is a foundational concept across mathematics, physics, spatial cognition, urban science, and embodied intelligence, yet these fields often treat

local-aiarxiv-cs-cl

Spectral Consistency-Guided Multiview Point Cloud Registration for Low-Overlap Scenes

arXiv:2609.12417v1 Announce Type: new Abstract: Multiview point cloud registration is particularly challenging in low-overlap scenes, where reliable correspondences are limited and incorrect pairwise

Split Conformal Prediction with Label-Shift-Adjusted Bayesian Scores

arXiv:2609.12386v1 Announce Type: new Abstract: Conformal prediction provides distribution-free uncertainty quantification under exchangeability. However, this assumption is violated by label shift, w

STAR: Sparse Tactile Representation Learning in Vision-Tactile-Language-Action Models for Dexterous Manipulation

arXiv:2609.12549v1 Announce Type: new Abstract: Dexterous manipulation requires coordinated multi-finger control and effective tactile feedback, yet learning these capabilities remains challenging due

applicationsarxiv-cs-ro

Statistical Mechanics of Semantic Compression

arXiv:2503.00612v2 Announce Type: replace-cross Abstract: The basic problem of semantic compression is to minimize the length of a message while preserving its meaning. This differs from classical not

researcharxiv-cs-cl

Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks

arXiv:2501.04234v2 Announce Type: replace-cross Abstract: Modern artificial intelligence is supported by machine learning models (e.g., foundation models) that are pretrained on a massive data corpus

SteerDuplex: Steerable Duplex Speech Dialogue Models

model-releasesarxiv-cs-cl

arXiv:2609.12623v1 Announce Type: cross Abstract: Full-duplex spoken dialogue models support low-latency turn taking, interruption handling, and backchanneling, yet a key capability remains underexplo

Subcortical Masks Generation in CT Images via Ensemble-Based Cross-Domain Label Transfer

arXiv:2508.11450v2 Announce Type: replace-cross Abstract: Subcortical segmentation in neuroimages plays an important role in understanding brain anatomy and facilitating computer-aided diagnosis of tr

SUCCESS-GS: Survey of Compactness and Compression for Efficient Static and Dynamic Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2512.07197v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view sy

Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders

arXiv:2505.13569v3 Announce Type: replace Abstract: The use of machine learning for modeling, understanding, and controlling large-scale physics systems is quickly gaining in popularity, with examples

SV-Cine: Diagnosis-Conditioned Segmentation of Single Ventricle Physiology via Generative Data Augmentation

arXiv:2609.12997v1 Announce Type: new Abstract: Single Ventricle Physiology (SVP) is a rare subtype of congenital heart disease characterized by the presence of a single functional cardiac ventricle w

SWARM: A Multilingual Human-Annotated Dataset for Russian Propaganda Detection in Search Engine Results

model-releasesarxiv-cs-cl

arXiv:2609.12653v1 Announce Type: new Abstract: Russian state propaganda spreads across many languages and online spaces. Yet, most computational work examines only one such space, usually social medi

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects

arXiv:2210.11003v3 Announce Type: replace-cross Abstract: We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multip

safetyarxiv-cs-lg

SynthSentry: Detecting Synthetic Data Contamination in Language Model Training Data

arXiv:2609.12353v1 Announce Type: new Abstract: Large language models trained recursively on their own or other models' outputs undergo model collapse, in which distributional tails and factual accura

applicationsarxiv-cs-cl

Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

model-releasesarxiv-cs-cl

arXiv:2609.13005v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are inc

Temporal Recurrence Favors Fewer Layers

arXiv:2609.12531v1 Announce Type: new Abstract: In streaming tasks, recurrent models can carry latent computation across time, allowing each update to build on representations produced earlier. This r

TestDG: Test-time Domain Generalization for Continual Test-time Adaptation

model-releasesarxiv-cs-cv

arXiv:2504.04981v3 Announce Type: replace Abstract: This paper studies continual test-time adaptation (CTTA), the task of adapting a model to constantly changing unseen domains in testing while preser

The AI industry has taken a doomer turn. What now?

This story appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. This weekend, Dario Amodei, CEO of Anthropic, posted an essay calling for

researchmit-tech-review