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WIDE: Wildcard Inference with Dynamic Expansion for Cross-Modal Generative Retrieval

arXiv:2609.03554v1 Announce Type: cross Abstract: Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation

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WireSeg-32K: A Physics-Grounded Synthetic Dataset for Wire Instance Segmentation

DGX agent

arXiv:2609.03102v1 Announce Type: new Abstract: Deformable linear objects such as wires and cables are difficult to segment because they are thin, highly deformable, and frequently self-occluded, whil

applicationsarxiv-cs-cv

4 Sept 2026

WISE: World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models

arXiv:2609.03681v1 Announce Type: new Abstract: Post-training VLA policies typically rely on supervised fine-tuning with costly expert demonstrations or reinforcement learning with expensive and poten

safetyarxiv-cs-ro

Witnesses Explain Anomalies

arXiv:2609.03826v1 Announce Type: cross Abstract: Unsupervised anomaly detection scores each point of an unlabelled, contaminated sample in a single pass, and increasingly must also explain why a poin

WorldReward: Reward Modeling for Camera-Conditioned World Models

model-releasesarxiv-cs-cv

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System

arXiv:2607.17544v1 Announce Type: cross Abstract: Real-time speech-to-speech translation (S2ST) systems must balance translation quality, latency, speech naturalness, and speaker consistency. Publicly

Xiaomi-TabLDM: A Tabular Foundation Model Technical Report

arXiv:2609.03880v1 Announce Type: new Abstract: We introduce Xiaomi-TabLDM, a tabular large data foundation model for classification and regression via in-context learning, which delivers superior pre

Y’all gonna get mad if I said I told you so …

model-releasesgary-marcus--x

Y’all gonna get mad if I said I told you so … Researchers argues OpenAI and Anthropic will never get us to AGI. 21 top researchers from Stanford, Oxford, DeepMind, CMU & Meta released a paper saying L

Local Ai

You can now run a 90M conversational LLM on the Sony PSP (hardware from 2004). Doesn't get more local than this.

Github link: https://github.com/thatblend/LLMPSP I wanted to see what the PSP can theoretically handle and I got my answer - a 90M model is about the max it can do without atrocious inference speeds.

local-air-localllama

You Can't Escape Your Own Activations : Evaluation Awareness and Multi-Agent Monitoring

arXiv:2609.03035v1 Announce Type: cross Abstract: LLM agents are increasingly deployed in multi-agent systems, where they can collude while keeping their actions benign. Output monitors designed to de

agentsarxiv-cs-lg

Tutorials

Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations

arXiv:2609.04174v1 Announce Type: new Abstract: 3D Foundation Models (3DFMs) such as VGGT have recently pushed the boundaries of 3D vision by predicting rich unified representations with feed-foward t

tutorialsarxiv-cs-cv

6 months ago, I started building an internal customer insights tool at Together AI. It pulls in our sales calls, slack channels, & support t…

6 months ago, I started building an internal customer insights tool at Together AI. It pulls in our sales calls, slack channels, & support tickets and turns them into searchable customer insights. Tod

agentstogether-ai--x

A Common Measure of Communication for Speech Brain-Computer Interfaces

arXiv:2609.02887v1 Announce Type: new Abstract: Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restoring speech for people with paralys

A Comparative Study of Graph Representations for GNN-Based Power Grid Control in L2RPN

arXiv:2609.02538v1 Announce Type: new Abstract: Graph construction is a critical but underexamined design choice in deep reinforcement learning for power grid control. We present a controlled experime

A computational approach to maximum likelihood thresholds for colored Gaussian graphical models

arXiv:2609.02382v1 Announce Type: cross Abstract: Gaussian graphical models (GGMs) are essential tools for interpretable structure learning. However, in high-dimensional, small-sample regimes, the ava

Hardware

A Computational Comparison of Fourier Spectral Differentiation and Spatial Automatic Differentiation in Periodic Physics-Informed Neural Networks

arXiv:2609.02110v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) commonly evaluate the spatial derivatives appearing in partial differential equation residuals using automatic

hardwarearxiv-cs-lg

A Data-Driven Multimodal Method for Early Detection of Coordinated Abnormal Behaviors in Live-Streaming Platforms

arXiv:2609.01649v1 Announce Type: cross Abstract: With the rapid growth of live-streaming e-commerce and digital marketing, abnormal marketing behaviors have become increasingly concealed and coordina

A Layered Taxonomy for Chinese Learner Grammatical Error Annotation

arXiv:2609.02153v1 Announce Type: new Abstract: Grammatical error annotation in Chinese learner writing requires labels that are both consistent and linguistically meaningful. This paper proposes a la

researcharxiv-cs-cl

A Physics-Consistent Benchmark for Contact-Rich Human-Robot Interaction in Assistive Care

model-releasesarxiv-cs-ro

arXiv:2609.02402v1 Announce Type: new Abstract: Conventional task-level evaluation asks whether a robot policy completes a specified action, but can miss failures that emerge only during physical huma

A Power Law in Logarithm's Clothing: On the Scalability of Graph-Based Vector Search

arXiv:2609.02143v1 Announce Type: cross Abstract: Most vector databases rely on graph-based indexes, notably HNSW and Vamana, for approximate nearest neighbor search. With embedding models widely adop

A Study of Conditional Diffusion Models for Open-Loop Control under Dry Friction and Stiction

model-releasesarxiv-cs-lg

arXiv:2609.01756v1 Announce Type: new Abstract: Diffusion models have recently emerged as expressive generative priors for planning and control. This paper studies Action Diffusion, an action-sequence

A Survey of Transformer-based Language Models with Focus on Efficiency

arXiv:2406.16893v3 Announce Type: replace-cross Abstract: The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (N

A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference

arXiv:2609.01679v1 Announce Type: new Abstract: The ability of AI systems to improve their behavior during deployment is becoming increasingly important. As inference moves beyond the static execution

agentsarxiv-cs-lg

Local Ai

A Top-Down Framework for Metric-Scale Athlete Localization from Single Broadcast Frames

arXiv:2609.02705v1 Announce Type: new Abstract: Accurate world-coordinate localization of athletes from single-frame broadcast footage is inherently challenging due to extreme scale disparities in ult

local-aiarxiv-cs-cv

A Tri-Agent Framework for Evaluating and Aligning Question Clarification Capabilities of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.02054v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in interactive systems where understanding user intent precisely is paramount. A key capability f

Applications

A Unified Particle Filter LSTM for Data-Driven Process Simulation

arXiv:2609.01967v1 Announce Type: new Abstract: Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model o

applicationsarxiv-cs-lg

A Unified Rate-Distortion Perspective on Vector, Product, and Scalar Quantization

arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding

safetyarxiv-cs-cv

A Universal Vibe? Finding and Controlling Language-Agnostic Informal Register with SAEs

model-releasesarxiv-cs-cl

arXiv:2603.26236v2 Announce Type: replace Abstract: While multilingual language models successfully transfer factual and syntactic knowledge across languages, it remains unclear whether they process c

Applications

Access to Astra is rolling out over the coming days. Starting today, enterprise customers in OpenAI's Daybreak Program can get access to Ast…

applicationscognition-ai--x

Access to Astra is rolling out over the coming days. Starting today, enterprise customers in OpenAI's Daybreak Program can get access to Astra. Read more on our blog: https://devin.ai/blog/gpt-6-astra

Accurate in space, unreliable in time: how LLMs represent national cultural change

arXiv:2609.01902v1 Announce Type: cross Abstract: Assessments of cultural alignment have become an important part of the development and improvement of large language models (LLMs). However, the major

Tutorials

Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method

arXiv:2408.02936v3 Announce Type: replace Abstract: Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires

tutorialsarxiv-cs-lg

Achieving Olympiad-Level Geometry Large Language Model Agent via Complexity Boosting Reinforcement Learning

arXiv:2512.10534v4 Announce Type: replace Abstract: Large language model (LLM) agents exhibit strong mathematical problem-solving abilities and can even solve International Mathematical Olympiad (IMO)

agentsarxiv-cs-ai

Act More, Decide Less: Skill-Guided Adaptive Action Chunking for Long-Horizon LLM Agents

arXiv:2609.02042v1 Announce Type: new Abstract: Large language model (LLM) agents for long-horizon interactive tasks typically follow a ReAct-style protocol, issuing one primitive action per LLM round

safetyarxiv-cs-lg

Action abstractions for amortized sampling

arXiv:2410.15184v2 Announce Type: replace-cross Abstract: As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignmen

Actor as Its Own Critic: Unifying Region Understanding and Localization via CycleGRPO

model-releasesarxiv-cs-cv

arXiv:2607.11581v2 Announce Type: replace Abstract: This paper introduces Actor as Its Own Critic, a unified reinforcement learning framework, Cycle Group Relative Policy Optimization (CycleGRPO), tha

AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents

arXiv:2606.21144v2 Announce Type: replace-cross Abstract: Long-term memory systems allow LLM agents to preserve information beyond a single context window, but most systems focus on storing and retrie

Local Ai

Adapting a Foundation Model for Lunar Surface Height Estimation

arXiv:2609.02448v1 Announce Type: new Abstract: Digital elevation models (DEMs) can provide accurate height information, making it invaluable for analyzing the lunar surface. As the European Space Age

local-aiarxiv-cs-cv

Applications

Addressing Trust in AI Systems through Education: A Didactic Perspective

arXiv:2609.02453v1 Announce Type: cross Abstract: Machine learning (ML) education faces two persistent and connected obstacles: many educational tools present ML as an opaque black box, which leaves l

applicationsarxiv-cs-ai

Advancing Accessible Underwater Robotics: The Mini-Girona I-AUV at RAMI 2025

arXiv:2609.02605v1 Announce Type: new Abstract: The Mini-Girona Intervention Autonomous Underwater Vehicle (I-AUV) represents an advancement in accessible underwater robotics, designed to bridge the g

agentsarxiv-cs-ro

Adversarial Stress Testing of Outlier Detection in Subjective Image Quality Assessment

arXiv:2509.06554v2 Announce Type: replace-cross Abstract: In subjective image and video quality assessment, observers rate or compare selected stimuli. Before calculating mean opinion scores (MOSs), u

AffectDelta: Beyond Emotion Labels for Image Editing

arXiv:2609.02616v1 Announce Type: new Abstract: Emotion-driven image editing aims to evoke a specified target emotion by modifying emotion-relevant visual cues in a source image, while preserving the

safetyarxiv-cs-cv

Agent Memory Is a Surface for Endogenous Authorization Laundering

arXiv:2609.01836v1 Announce Type: cross Abstract: Long-running LLM agents rely on persistent memory to carry state across interactions, including permissions, restrictions, and revocations. When memor

Agentic AI is compressing attacker intrusion timelines to minutes

Artificial intelligence has moved from a curiosity in the threat landscape to a working part of the intrusion, and agentic adversaries have infiltrated extortion campaigns, espionage operations and ha

agentssiliconangle

Agents That Model Agents: Five Principles Toward a Theory of Mind for 6G Networks

arXiv:2609.01779v1 Announce Type: cross Abstract: Future 6G networks will rely on Large Language Model (LLM) agents to manage the Radio Access Network (RAN). However, current architectures assume inte

Aggregating Neighbor Embedding Projection and Rank-Based Manifold Learning for Image Retrieval

arXiv:2609.01963v1 Announce Type: new Abstract: Content-based image retrieval (CBIR) has advanced significantly with deep learning, yet effectively ranking similar images remains challenging, particul

researcharxiv-cs-cv

AGI Maze Prediction Datasets: A Compact Benchmark for Learning World Dynamics with Transformers

arXiv:2609.02339v1 Announce Type: cross Abstract: World modeling requires a predictive model to maintain and update an internal state adequate for reasoning about the consequences of actions. We intro

AI agents reshape consensus formation in human groups

arXiv:2609.02122v1 Announce Type: new Abstract: As large language model (LLM) agents shift from tools to participants in human groups, a fundamental question for collective behavior is how their growi

agentsarxiv-cs-cl

AI Contextual Measurement for Recovering Individual and Group-Level Effects: Validation Against Survey Measures and an Occupational Application

arXiv:2609.02821v1 Announce Type: new Abstract: Researchers increasingly use artificial intelligence to construct measures of social, organizational, and occupational characteristics that are absent f