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arXiv:2609.22260v1 Announce Type: cross Abstract: A large audio language model (LALM) attaches a speech front end to a text language model (LM) that is already safety-aligned. When such a model refuse

local-aiarxiv-cs-cl

Tutorials

CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model

Content type

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DGX agent

arXiv:2609.23184v1 Announce Type: new Abstract: Embodied world models learn to predict future physical dynamics from visual observations and control signals, where physical knowledge is implicitly ent

tutorialsarxiv-cs-cv

22 Sept 2026

Causilo Technical Report

model-releasesarxiv-cs-lg

arXiv:2609.22866v1 Announce Type: new Abstract: We introduce Causilo, a tabular foundation model (TFM) that combines frontier predictive performance with exceptionally fast inference. On TabArena, Cau

CCTU: A Benchmark for Tool Use under Complex Constraints

arXiv:2603.15309v2 Announce Type: replace Abstract: Solving problems through tool use under explicit constraints constitutes a highly challenging yet unavoidable scenario for large language models (LL

CE^4L: Continual Ego, Exo, and Ego-Exo Learning

arXiv:2609.23492v1 Announce Type: new Abstract: Perception for embodied agents is video-based, often multi-view (ego, exo, or both), and inherently continual, with simultaneous task and viewpoint shif

Agents

Characterizing Wildlife Response to Biomimetic and Conventional Underwater Vehicles

arXiv:2609.22594v1 Announce Type: new Abstract: Autonomous underwater vehicles (AUVs) are a promising alternative to divers for scalable collection of natural ocean ecology data. However, these robots

agentsarxiv-cs-ro

Local Ai

CHART: A Harness-Rotation Curriculum for Harness-Robust Search Agents

arXiv:2609.22247v1 Announce Type: new Abstract: Search agents are usually trained under a single harness. But once an agent is deployed in a real application, its harness is frequently updated (e.g.,

local-aiarxiv-cs-lg

ChartJudgeBench: Evaluating LMM Judges for Chart-to-Code Generation

arXiv:2609.24210v1 Announce Type: new Abstract: Building strong chart-to-code systems increasingly relies on reinforcement learning, whose effectiveness depends critically on the quality of the reward

Agents

Checkpoints Are Not Enough: Trust Calibration in CoSLR, a Human-AI System for Systematic Literature Reviews

arXiv:2609.22248v1 Announce Type: new Abstract: Systematic Literature Reviews (SLRs) are essential for evidence-based research but remain time-consuming, requiring researchers to manage large volumes

agentsarxiv-cs-cl

ChemCLIR-Bench: Benchmarking Cross-Lingual Information Retrieval in Multilingual Chemical Patents

arXiv:2609.23231v1 Announce Type: new Abstract: Cross-lingual information retrieval (CLIR) is increasingly important in multi-national industries, where critical technical evidence may exist in a diff

CHOREO: Every Humanoid Skill as a Trajectory

arXiv:2609.22274v1 Announce Type: new Abstract: Recent advances in humanoid robotics have produced diverse skills through reinforcement learning, motion imitation, and generative modeling. Yet these c

researcharxiv-cs-ro

Chronologic: Measuring Language Models' Ability to Represent the Past

arXiv:2609.23178v1 Announce Type: new Abstract: Language models are appealing tools for research on the past. But to trust the evidence a model provides, researchers need to know whether its responses

CIG-MAE: Cross-Modal Information-Guided Masked Autoencoder for Self-Supervised WiFi Sensing

arXiv:2512.04723v2 Announce Type: cross Abstract: Human Action Recognition using WiFi Channel State Information (CSI) has emerged as an attractive alternative to vision-based methods due to its ubiqui

Circuit-Diff: Factual Edit-based Intervention Method for Localizing Knowledge in Attribution Graphs

model-releasesarxiv-cs-lg

arXiv:2609.23892v1 Announce Type: new Abstract: Mechanistic interpretability defines features as the fundamental units of a neural network and circuits as the weighted subgraphs that carry out its com

Circuit Hypernetworks for Quantum-Augmented Diffusion Language Models

arXiv:2609.24657v1 Announce Type: cross Abstract: Language models can be adapted by changing the computations applied to individual tokens. Quantum circuits offer one such approach, but evaluating wid

Classification with Abstention Under Class-Conditional Error Constraints

arXiv:2609.22632v1 Announce Type: new Abstract: We study binary classification with abstention under separate class-conditional error constraints, with the objective of minimizing abstention while kee

Classifier-Free Guidance in Flow Matching: Non-Autonomous Potentials, Overshoot, and Posterior-Mean Control

arXiv:2609.24287v1 Announce Type: new Abstract: Classifier-free guidance (CFG) improves conditional generation in Flow Matching, but strong guidance can distort the generated distribution and reduce d

safetyarxiv-cs-cv

Claude Opus 5.5, GPT-6 Sol, GPT-6 Luna, and a new price war

model-releasessimon-willison

Yesterday was Grok 4.7 (pelicans) and MiMo v2.6 Flash/Pro (more pelicans). Today Anthropic released Claude Opus 5.5, and around an hour later OpenAI released GPT-6 Sol and GPT-6 Luna. It's going to ta

Claude Opus 5.5 is now available as the Standard effort level in Perplexity Computer. On our WANDR benchmark, it scored 0.610 at $4.13 per t…

model-releasesperplexity--x

Claude Opus 5.5 is now available as the Standard effort level in Perplexity Computer. On our WANDR benchmark, it scored 0.610 at $4.13 per task, slightly outperforming Claude Fable 5.1 while costing 6

Claude Opus 5.5 is now available on AWS

model-releasesaws-ml-blog

Claude Opus 5.5, Anthropic's most capable Opus model for agentic coding, knowledge work, and long-running tasks, is now available on Amazon Bedrock and Claude Platform on AWS. This post covers what's

Claude Opus 5.5 will be the first Opus meant to fall back to a less capable model for 'a small set of capabilities related to the developmen…

model-releasesclem-delangue--x

Claude Opus 5.5 is the first Opus variant that can automatically fall back from its main model to a reduced‑capability version when executing a small set of specialized tasks associated with frontier

CleanScore: Black-Box Benchmark Audits with Negative Controls and Sensitivity Bounds

model-releasesarxiv-cs-lg

arXiv:2609.22183v1 Announce Type: new Abstract: Public benchmark scores may reflect skill, prior exposure to the questions, or both, and for most models the training data are unknown. We present Clean

CLEAR: Complex Learned Explicit Analytical Regularization for Ultra-Accelerated 4D Flow CMR Reconstruction

arXiv:2609.22950v1 Announce Type: new Abstract: While compressed-sensing regularizers enable interpretable reconstruction of 4D Flow CMR through transparent variational objectives, their hand-crafted

Climate Variability Modulates the Impact of Price Spikes on Food Insecurity

arXiv:2609.24394v1 Announce Type: new Abstract: Climate variability influences whether a market disruption escalates into a food crisis, yet broad climate patterns like El Nino, tracked months before

Clinical Domain Classification from Medical Transcriptions

arXiv:2609.22734v1 Announce Type: new Abstract: Clinical domain classification plays an important role in organizing and analyzing large volumes of unstructured medical text. However, medical transcri

researcharxiv-cs-cl

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

arXiv:2504.14280v2 Announce Type: replace Abstract: As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for improving model robustness across diverse

safetyarxiv-cs-cv

CLOOPD: Closing the Learner Loop in On-Policy Distillation

arXiv:2609.24141v1 Announce Type: new Abstract: On-policy distillation (OPD) pays twice for each fresh batch: the student generates trajectories and a stronger teacher scores them. Existing methods im

safetyarxiv-cs-lg

Closed-Circuit Television Data as an Emergent Data Source for Urban Rail Platform Crowding Estimation

arXiv:2508.03749v2 Announce Type: replace Abstract: Accurately estimating urban rail platform occupancy can support more informed operational decision-making by transit agencies, particularly during p

Closing the Speech-Text Gap with Limited Audio for Effective Domain Adaptation in LLM-Based ASR

arXiv:2604.06487v2 Announce Type: replace Abstract: Conventional end-to-end automatic speech recognition (ASR) systems rely on paired speech-text data for domain adaptation. Recent LLM-based ASR archi

safetyarxiv-cs-cl

Tutorials

Clustering-Based Collective Anomaly Detection in IoT Systems: A Graph Neural Network Approach

arXiv:2609.22166v1 Announce Type: new Abstract: The rapid advancement of Internet of Things (IoT) technology has led to the widespread deployment of smart, interconnected devices across a range of dom

tutorialsarxiv-cs-lg

Local Ai

CMAMBADEPTH: Self-supervised Monocular Depth Estimation with Channel Mamba and Hybrid Attention

arXiv:2609.24494v1 Announce Type: new Abstract: Accurate monocular depth estimation serves as a core enabler for single camera scene understanding. However, existing self-supervised monocular depth es

local-aiarxiv-cs-cv

CNA: An AI-Oriented Comprehensive Normalized Assessment for Healthy Status and Application to Optimize RRT Strategies by Reinforcement Learning

arXiv:2609.22232v1 Announce Type: new Abstract: Millions worldwide require Renal Replacement Therapy (RRT) as a treatment essential for survival. However, optimizing RRT strategies via AI is challengi

Hardware

Co-occurrence Patterns of LoRA Adapters in Production Diffusion Model Inference Services

arXiv:2609.23321v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become a key technology for serving large-scale personalized large language models and diffusion models in the cloud. H

hardwarearxiv-cs-lg

Agents

CoaG: Cylinders on a Grid: Coarse 3D Layout Control for Video Generation

arXiv:2609.24208v1 Announce Type: new Abstract: We ask how little geometry a person has to draw to control both where people stand and where the camera moves in a generated video. Our answer is a grou

agentsarxiv-cs-cv

Industry

Cognex agrees to acquire robotics and 3D computer vision company RealSense in a ~600M deal, including 500M in cash; Intel spun off RealSense in July 2025 (Sophie Shulman/CTech)

Sophie Shulman / CTech: Cognex agrees to acquire robotics and 3D computer vision company RealSense in a ~600M deal, including 500M in cash; Intel spun off RealSense in July 2025 — The Haifa-based robo

industrytechmeme

Cognition to Control - Multi-Agent Learning for Human-Humanoid Collaborative Transport

arXiv:2603.03768v2 Announce Type: replace Abstract: Full-stack human-robot collaboration (HRC) can become brittle when replacing a planner, partner model, coordination policy, or controller changes th

safetyarxiv-cs-ro

Cognitive Action Reasoning for Proactive Robots from Human-Centered Multimodal Observations

arXiv:2609.23486v1 Announce Type: cross Abstract: Robots operating in human-centered environments are typically designed to execute explicit instructions, and most robot-learning datasets likewise pai

Collaborative Streaming Anomaly Detection with Interactive Explanations and Ensemble Consensus

arXiv:2609.23883v1 Announce Type: new Abstract: We present a collaborative streaming anomaly detection system for high-speed data streams that explicitly integrates human analysts into the decision lo

Collapse, Not Complexity: Failure-Conditioned Decomposition Repair for End-to-End Document Parsing

arXiv:2609.23592v1 Announce Type: cross Abstract: End-to-end document parsers increasingly offer an optional reasoning mode for complex pages. On a 180-page entropy-stratified discovery sample with on

Colon3R: Cross-Domain 3D Reconstruction from Monocular Colonoscopic Video

arXiv:2609.23961v1 Announce Type: new Abstract: Monocular colonoscopic 3D reconstruction is important for surgical robotic colonoscopy, but remains challenging due to weak texture, specular reflection

Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models

arXiv:2301.12254v5 Announce Type: replace-cross Abstract: Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive litera

Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation

arXiv:2609.22896v1 Announce Type: new Abstract: Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo.

Tutorials

Common Cause, Not Cross-Attention: Blocking Visual Shortcuts in Audio-Video Generation

arXiv:2609.22361v1 Announce Type: new Abstract: Joint audio--video generators are trained on data in which what an event looks like and what it sounds like are strongly, often spuriously, correlated:

tutorialsarxiv-cs-lg

Commonsense-Grounded Path Planning from Abstract Instructions

model-releasesarxiv-cs-ro

arXiv:2609.22813v1 Announce Type: new Abstract: We present commonsense ranked search (CoRS), a novel path planner that turns an abstract instruction into a route that follows commonsense. While existi

Compact Low-Cost Hyperspectral Imaging via Angular-to-Spectral Diversity Conversion

arXiv:2609.23619v1 Announce Type: new Abstract: Snapshot hyperspectral imaging avoids sequential scanning, but systems that jointly achieve stable reconstruction, low cost, and compact optics remain l

Comparative Analysis of State-of-the-Art Foundation Models for Sleep Analysis Under Channel Reduction

arXiv:2609.22105v1 Announce Type: cross Abstract: Automatic sleep staging from polysomnography (PSG) is a well-studied task, but PSG itself is expensive, clinic-based, and burdensome to manually score

Comparative Performance and Parameter-Efficient Adaptation of DINOv2 for Active Trachoma Classification

arXiv:2609.23832v1 Announce Type: new Abstract: Automated grading of conjunctival photographs could reduce the cost and variability of trachoma prevalence surveys, but the relative value of modern pre

Comparative Study of Quantum and Classical Machine Learning Models in Binary Classification

arXiv:2609.23476v1 Announce Type: cross Abstract: A potential path forward is Quantum Machine Learning (QML), which aims to leverage quantum computing in conjunction with classical machine learning to