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CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception

arXiv:2609.03818v1 Announce Type: new Abstract: Collaborative perception enhances environment understanding through multi-agent information sharing, but its performance in real-world scenarios is cons

agentsarxiv-cs-ai

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Model Releases

Check out this week’s shipping recap: — Gemini 3.8 Flash, our most intelligent workhorse model yet, delivers upgrades across coding, agentic…

DGX agent

Check out this week’s shipping recap: — Gemini 3.8 Flash, our most intelligent workhorse model yet, delivers upgrades across coding, agentic workflows, and critical multi-step reasoning. — Gemini 3.8

model-releasesgoogle-ai--x

4 Sept 2026

Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer…

model-releasesboris-cherny--x

Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer proof assistants like Lean can verify—can help. Last month,

Chiaroscuro for Emotions: A Contrastive Emotion Benchmark Grounded in Appraisal Theory

arXiv:2609.03394v1 Announce Type: new Abstract: Emotion recognition benchmarks often predict one emotion per text, missing many real-world scenarios where two people arrive at opposing emotions from a

Cisco remakes the edge for AI’s data-heavy future

The modern edge computing platform has arrived. Before the explosion of artificial intelligence, edge computing sites were generally regarded as a back-end support function, smaller and more remote co

agentssiliconangle

Clean Engineering, Unstable Measurement: A Preregistered Reliability Failure of Black-Box LLM Observers on Shared Endpoints

arXiv:2609.04198v1 Announce Type: new Abstract: Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rare

CoFiE: Coarse-to-Fine Evidence Selection for Efficient Streaming Video Understanding

arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con

researcharxiv-cs-cv

Common-Witness Certificates and Sharp Feature Bounds for Counterfactual Image Auditing

arXiv:2609.03973v1 Announce Type: new Abstract: An image editor may satisfy every regional plausibility constraint separately even when no single latent explanation fits the complete output. We formal

Comparing Retrieval Methods for Academic Advisor Discovery: A Six-Method Study of 768 CS Faculty Profiles Across 9 US Universities

arXiv:2609.03901v1 Announce Type: cross Abstract: We present a comparative evaluation of six information retrieval methods for the task of academic advisor discovery: ranking CS faculty members by rel

Applications

Compile by Training: Turning Natural-Language Specifications into Local Neural Functions

arXiv:2609.04199v1 Announce Type: cross Abstract: Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduce

applicationsarxiv-cs-ai

Complete Identification of Deep ReLU Networks through {L}ukasiewicz Logic

arXiv:2602.00266v2 Announce Type: replace Abstract: Two deep ReLU networks can have entirely different architectures and parameters, yet realize the same function. We provide a complete characterizati

Computing stable configurations of confined smectic liquid crystals with a deep variational framework

arXiv:2609.03389v1 Announce Type: cross Abstract: Smectic liquid crystals are layered liquid-crystalline phases characterized by orientational order and periodic density modulation. Although their str

safetyarxiv-cs-lg

Concept of a Sensor Test Environment for Dusty Agricultural Conditions

arXiv:2609.03895v1 Announce Type: new Abstract: Dust in agriculture presents a significant challenge for autonomous agricultural machinery. Dust can impair the performance of sensors and algorithms. T

agentsarxiv-cs-cv

Conditioning Degenerate Diffusion Models

arXiv:2609.04090v1 Announce Type: new Abstract: Current conditioned generative models heavily rely on score functions for guidance during training. When the generative model is a diffusion process wit

researcharxiv-cs-lg

Constant regret in general games via higher-order optimism

arXiv:2609.04113v1 Announce Type: new Abstract: We introduce an uncoupled learning algorithm which, when employed by all players of an arbitrary N-player normal form game with up to K actions per play

researcharxiv-cs-lg

Contamination Inflates Scores but Rarely Reorders Large Language Model Leaderboards

arXiv:2609.02899v1 Announce Type: new Abstract: Benchmark contamination, the leakage of test items into training data, is widely described as a threat to the reliability of large language model (LLM)

Contextual Tamil Spelling and Grammar Correction Using Progressively Fine-Tuned Sequence-to-Sequence Transformers

arXiv:2609.03273v1 Announce Type: new Abstract: Tamil spell and grammar correction is challenging because Tamil is an agglutinative low-resource language with rich verbal morphology, complex sandhi (p

Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a

Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks

arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent

CORE: Improving Compositional Reasoning in MLLM Embedding via Reranker Distillation

model-releasesarxiv-cs-ai

arXiv:2609.04083v1 Announce Type: cross Abstract: MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes containing the same concepts but different

Corner Cases: Headland Coverage Path Planning for Autonomous Driving in Arable Farming

arXiv:2609.04103v1 Announce Type: new Abstract: This paper presents a new method for headland coverage path planning for arable fields. Several earlier approaches suggest covering the headland with ne

agentsarxiv-cs-ro

Correlated initialization of deep residual networks

arXiv:2609.03589v1 Announce Type: cross Abstract: We study the large-depth behavior of residual networks whose weights are correlated across layers at initialization. Our results confirm and extend a

researcharxiv-cs-lg

Counterexamples as Feedback for Agent Self-Correction

arXiv:2609.02892v1 Announce Type: cross Abstract: Single-turn code-generation metrics understate a central property of deployed agents: whether they can repair a wrong artifact after receiving concret

agentsarxiv-cs-ai

Counterfactual Fairness Audits of Multi-Step Clinical LLM Agents Require a Measured Per-Action Instability Floor

arXiv:2609.03221v1 Announce Type: new Abstract: Counterfactual audits are the standard tool for checking whether a clinical agent treats demographically distinct but clinically identical patients diff

Counterfactual Routing Using Integer Programming with Constraint Generation

arXiv:2609.03707v1 Announce Type: new Abstract: We present our submission to the IJCAI 2025 'Counterfactual Routing Competition' (CRC 25). The goal of the competition is to find counterfactual explana

Counting Animals in Camera-Traps Image Sequences without Count Labels: Winning Solution to the iWildCam 2021 Challenge

model-releasesarxiv-cs-cv

arXiv:2609.03233v1 Announce Type: new Abstract: Camera traps have become an essential tool for wildlife monitoring, motivating the development of computer vision methods for the automated extraction o

Coupled Scaling: A Representational Accessibility Framework for Neural Scaling Laws

arXiv:2609.03533v1 Announce Type: new Abstract: Existing theories derive neural scaling from data geometry or a specified data-model spectrum, but systems trained on the same data can scale differentl

Coupled Tensor-Tensor Completion Method with Applications in Drug Repurposing

arXiv:2609.03190v1 Announce Type: cross Abstract: Many biomedical challenges can be posed as tensor completion problems where the observed entries of a multidimensional array (a tensor) are used to im

Applications

CRAW: Codec Robust Audio Watermarking

arXiv:2609.03107v1 Announce Type: cross Abstract: Recent advances in generative speech models have made it increasingly difficult to distinguish authentic from synthetic audio, enabling new forms of f

applicationsarxiv-cs-lg

Crazy to see this. I have spent years saying that GenAI was unreliable and we can’t trust it. The fact that it cannot be trusted to follow i…

Crazy to see this. I have spent years saying that GenAI was unreliable and we can’t trust it. The fact that it cannot be trusted to follow instructions is a core part of the issue, as I have been poin

safetygary-marcus--x

CROCODIL: Cross-Model Code Editing with LLMs

arXiv:2609.03894v1 Announce Type: new Abstract: Large language models (LLMs) have become ubiquitous tools for code generation and editing. However, development teams often use multiple LLM assistants.

safetyarxiv-cs-cl

Cross-Dataset Transfer and Reliability of Explainable Artificial Intelligence for RhythmFormer Remote Photoplethysmography

arXiv:2609.03663v1 Announce Type: cross Abstract: Background. Remote photoplethysmography estimates the cardiovascular pulse from facial video, and its explanations have rested on inspecting heatmaps

CulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning

model-releasesarxiv-cs-ai

arXiv:2609.03526v1 Announce Type: new Abstract: Multimodal language models achieve near-ceiling scores on food recognition benchmarks, yet it remains unclear whether this success reflects genuine cult

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

Learn how to customize an Amazon Bedrock knowledge base for large, complex documents by combining the high-accuracy text extraction of Amazon Textract with the generative AI of Amazon Bedrock. This po

tutorialsaws-ml-blog

Dalek: A Constructive Agent Machine

arXiv:2609.03546v1 Announce Type: new Abstract: We present Dalek, a closed machine designed for agents that realizes self-maintenance, self-evolution, self-reproduction, and self-organization on any s

agentsarxiv-cs-ai

Dancing with REEM-C: A robot-to-human physical-social communication study

arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo

tutorialsarxiv-cs-ro

Data-efficient Kernel Methods for Learning Hamiltonian Systems

arXiv:2509.17154v2 Announce Type: replace-cross Abstract: Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many

Data Market Design through Deep Learning

arXiv:2310.20096v2 Announce Type: replace-cross Abstract: The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expect

tutorialsarxiv-cs-ai

DE-Venus: A Data-Efficient RLVR Framework for Large Language Models

arXiv:2609.03324v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves large language model reasoning, but its practical scaling is constrained by expensive on-

safetyarxiv-cs-lg

Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring

arXiv:2508.15038v2 Announce Type: replace-cross Abstract: Wildlife field operations demand efficient parallel deployment methods to identify and interact with specific individuals, enabling simultaneo

safetyarxiv-cs-ai

Decoupled Analysis-Judging: An Automated Creativity Evaluator Using LLMs in Complex Multi-step Creativity Tasks

arXiv:2609.03432v1 Announce Type: new Abstract: Automated evaluation of creativity tasks remains challenging for LLM-as-a-Judge, as LLM is susceptible to biases such as verbosity bias and leniency bia

safetyarxiv-cs-cl

Decoupling Turn-Taking from Semantics: A Decoupled Data Approach for Finite-State-Machine-Based Full-Duplex Dialogue

arXiv:2609.03321v1 Announce Type: new Abstract: The Neural Finite State Machine (NFSM) framework offers a pragmatic path to full-duplex dialogue by serializing turn-taking control and response generat

agentsarxiv-cs-cl

Deploy a multimodal WhatsApp ordering assistant with Amazon Bedrock AgentCore

Learn how to deploy a multimodal WhatsApp ordering assistant that takes customer orders through text, voice notes, and real-time voice calls on a single business number, built on Amazon Bedrock AgentC

tutorialsaws-ml-blog

Designing lifecycle policies for AgentCore memory

Long-running AI agents accumulate outdated memories that degrade quality and create compliance risk. Learn how to design memory lifecycle policies for Amazon Bedrock AgentCore: scoring, consolidating,

agentsaws-ml-blog

Despite everything that has happened, OpenAI has seemingly decided to stay competitive by burning down the only meaningful bit of safety ass…

Despite everything that has happened, OpenAI has seemingly decided to stay competitive by burning down the only meaningful bit of safety assurance we actually have today - CoT monitoring. Completely d

safetygary-marcus--x

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

arXiv:2412.08414v2 Announce Type: replace Abstract: Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest

researcharxiv-cs-cl

DIAL-GS: Dynamic Instance Aware Reconstruction for Label-free Street Scenes with 4D Gaussian Splatting

arXiv:2511.06632v2 Announce Type: replace Abstract: Urban scene reconstruction is critical for autonomous driving, enabling structured 3D representations for data synthesis and closed-loop testing. Su

agentsarxiv-cs-cv

Differentiable Hybrid Modelling for Learning and Optimising Chemical Transport Processes from Experimental Data

arXiv:2609.04011v1 Announce Type: cross Abstract: Reliable transport models are essential when modelling and optimising many chemical engineering processes, yet, most models assume hand-picked constit

safetyarxiv-cs-lg