model releases

Bootstrapping Audiovisual Speech Recognition in Zero-AV-Resource Scenarios

arXiv:2603.08249v2 Announce Type: replace-cross Abstract: Audiovisual speech recognition (AVSR) combines acoustic and visual cues to improve transcription robustness under challenging conditions but r

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Model Releases

Breaking the Uniformity Trap: Scaling Video Diffusion Model via SplitMoE

DGX agent

arXiv:2609.38140v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE), popularized by large language models, is a promising paradigm for scaling visual generative models. However, conventional to

model-releasesarxiv-cs-ai

30 Sept 2026

Byzantine-Robust Federated Representation Learning

arXiv:2609.36660v1 Announce Type: new Abstract: We study federated learning (FL) with adversarial clients, where the goal is to minimize the average loss of the honest (non-adversarial) clients withou

Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models

arXiv:2609.36828v1 Announce Type: new Abstract: Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences wit

Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting

arXiv:2609.35795v1 Announce Type: cross Abstract: Asthma deterioration forecasting must remain reli- able when patient populations, sensor ecosystems, and available modalities change across cohorts. E

CALIBUDGET: Calibration-Guided Source Allocation for Fixed-Budget Mixed-Reasoning Adaptation

arXiv:2609.36721v1 Announce Type: new Abstract: Fixed-budget adaptation from heterogeneous data sources requires deciding not only how much data to use, but how much exposure each source receives. Siz

Can Agents Design Libraries for Agents?

arXiv:2609.36730v1 Announce Type: new Abstract: Agents increasingly build on code written by other agents, and they reimplement rather than reuse, growing the codebases later agents must work in. To m

Can AI Scientists Change Their Minds? Prior-Evidence Conflict in Synthetic Universes

arXiv:2609.36726v1 Announce Type: new Abstract: Can a scientific agent distinguish a law it inferred from evidence from one it merely recognizes? We introduce Synthetic Universes, a controlled benchma

Can Language Models Learn to Forecast Stock Prices

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

Can Multimodal Large Language Models Generate and Detect Multimodal Social Media Fake News?

arXiv:2609.35809v1 Announce Type: cross Abstract: The rapid advancement of generative AI raises concerns about the misuse of Multimodal LLMs (MLLMs) for large-scale disinformation campaigns on social

Causal and Interpretable Structures in LLM Compositional Tasks

arXiv:2609.35970v1 Announce Type: cross Abstract: Large language models are able to solve tasks whose answers depend on not only individual input tokens, but also on relations among them. How is such

Causal-EVC: Breaking Emotional Spurious Causality via Spatiotemporal Grounding and Counterfactual Intervention

model-releasesarxiv-cs-cv

arXiv:2609.36776v1 Announce Type: new Abstract: Emotional Video Captioning aims to generate factually accurate and emotionally empathetic descriptions. While recent methods have recognized the importa

Causal pieces: analysing and improving spiking neural networks piece by piece

arXiv:2504.14015v2 Announce Type: replace-cross Abstract: We introduce 'causal pieces', a novel concept for analysing spiking neural networks (SNNs), inspired by 'linear pieces' used to study expressi

CF-LoRA: Decoupled Factor Aggregation and Adaptation-Aware Client Clustering for Federated LoRA Fine-Tuning

arXiv:2609.36986v1 Announce Type: new Abstract: Federated LoRA fine-tuning enables parameter-efficient adaptation of pre-trained models without sharing private data, but suffers from two fundamental m

Channel-Dependent State Space Model for Multivariate Time Series Forecasting

arXiv:2609.36453v1 Announce Type: cross Abstract: Multivariate time series forecasting (MTSF) is critical across many real-world domains. Existing deep learning approaches fall into two paradigms with

Character Training for Risk-Averse Agents

arXiv:2609.38093v1 Announce Type: new Abstract: Risk aversion in resources could prevent misaligned AI agents from causing catastrophic harm. Misaligned but risk-averse agents would tend to favor safe

Cheap to Hypothesize, Costly to Verify: The Defense Surface of Agentic Vulnerability Discovery

arXiv:2609.35909v1 Announce Type: cross Abstract: Autonomous LLM agents turn vulnerability discovery into a repository-scale search: they generate many vulnerability hypotheses but can verify only a s

CheatBench: Measuring Reward Gaming in AI Agents

arXiv:2609.36308v1 Announce Type: new Abstract: Reinforcement learning has helped AI agents solve increasingly difficult tasks, but high rewards do not always reflect the work users intended. In recen

CI-PINN: Causal Integral Physics-Informed Neural Network for Solving Evolution Equations

arXiv:2609.36615v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) solve partial differential equations (PDEs) by incorporating governing physical laws into the training loss.

CineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles

arXiv:2609.36218v1 Announce Type: cross Abstract: Large language models are increasingly evaluated in specialized domains such as law, medicine, software engineering, and cybersecurity, yet film remai

CipherGenome: Homomorphic Inference for Genomic Mixture-of-Experts

arXiv:2609.35883v1 Announce Type: cross Abstract: Genome foundation models are growing into sparse mixture-of-experts (MoE) networks whose expert weights no longer fit on the machines that hold the se

cktFormer: Transformer-Based Approach for Automated Analog Circuit Design

arXiv:2609.36752v1 Announce Type: new Abstract: Circuit design is a complex and iterative process that requires expertise in electronic engineering. It involves selecting components while meeting perf

Closed-Form Cartesian Forward Kinetostatics for Spatial Multi-Segment Tendon-Driven Continuum Robots

model-releasesarxiv-cs-ro

arXiv:2609.36495v1 Announce Type: new Abstract: Forward kinetostatics of spatial tendon-driven continuum robots typically requires a nonlinear equilibrium solve for each actuation input. This paper de

Cloud CISO Perspectives: How cybersecurity startups can win CISOs

model-releasesgoogle-cloud-ai

Welcome to the second Cloud CISO Perspectives for September 2026. Today, Alicja Cade and Nick Godfrey, senior directors, Office of the CISO, share their guidance for cybersecurity startups on how to w

Code4Scene: Benchmarking Coding Agents for Constructing and Editing 3D Scenes

arXiv:2609.36777v1 Announce Type: new Abstract: Frontier coding agents can now write and execute code that authors 3D environments, but whether they reliably understand 3D structure and precisely cont

CoMemBench: Benchmarking Collaborative Memory Boundaries across Multi-Agent Workflow Topologies

arXiv:2609.32192v2 Announce Type: replace Abstract: Multi-agent workflows require task-relevant information to be shared across agents, while irrelevant, stale, unverified, or incompatible information

Compiling Learning Problems into Adaptation Programs for Language Models

arXiv:2609.37371v1 Announce Type: cross Abstract: Model adaptation is typically governed by a fixed recipe, even though different update programs can produce substantially different behavioral outcome

Complexity-Aware Evaluation of LLM Comprehension

arXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior

CompOrca: Corpus-Scale Compliance Labelling of Instruction-Tuning Data

arXiv:2609.37807v1 Announce Type: new Abstract: Studying how fine-tuning shapes refusal and noncompliance behaviour requires identifying training examples that refuse, evade or otherwise fail to fulfi

Concealing LLM-Based Multi-Agent Topology via Phantom Structure Injection

arXiv:2609.37567v1 Announce Type: cross Abstract: Driven by the rapid advancement of large language models (LLMs), LLM-based multi-agent systems (MAS) have emerged as a powerful paradigm for collabora

Constructing Challenging Browser-Use Tasks by Controlled Environment Interventions

arXiv:2609.35814v1 Announce Type: cross Abstract: As browser-use agents improve, benchmarks keep pace by collecting new tasks, websites, and applications, often making tasks longer or more novel. This

ContextRender: From Execution Dependencies to Agent Context

arXiv:2609.37743v1 Announce Type: new Abstract: LLM agents performing long-horizon tasks accumulate tool results that later steps may need. Passing the full history to every invocation is costly even

Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces

arXiv:2609.38107v1 Announce Type: cross Abstract: Chain-of-thought traces are widely read as records of how models reach their answers, informing debugging, agent auditing, and claims about reasoning.

Corruption-Robust Sparse Linear Contextual Bandits with Knapsack Constraints

arXiv:2609.37189v1 Announce Type: new Abstract: We study sparse linear contextual bandits with knapsack constraints under joint reward and consumption corruption. Consumption corruption creates a chal

CoSec: Benchmarking Agent Security in Communities

arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community bound

Counterfactual Probing for Parallel Unmasking with Hidden Forest Structure

arXiv:2609.37841v1 Announce Type: new Abstract: Masked generative models offer parallel token prediction, but accurate parallel sampling must account for dependencies among tokens. When dependencies a

CounterSteer: Suppressing Indirect Prompt Injection with Activation Steering

arXiv:2609.36570v1 Announce Type: cross Abstract: Indirect prompt injection makes an LLM agent treat untrusted retrieved text as instructions. We present CounterSteer, an inference-time defense that s

CoVLM-Bench: A Real-World Benchmark for Cooperative Driving Question Answering and Planning

model-releasesarxiv-cs-cv

arXiv:2609.35823v1 Announce Type: new Abstract: Vision-language models (VLMs) have made substantial progress in autonomous driving, but their success has primarily been studied in ego-centric scenes.

CredWise: A Controlled Agentic Decision-Intelligence Framework for Explainable and Auditable Credit-Risk Assessment

arXiv:2609.37223v1 Announce Type: new Abstract: Credit-risk prediction is important in banking, but a prediction alone does not explain why an applicant is risky or how it should be combined with othe

CRJudgeBench: Can AI Detect Plausible but Invalid Code Reviews?

arXiv:2609.37216v1 Announce Type: cross Abstract: Large language models can generate plausible code-review comments, but such comments may contain technically incorrect claims that mislead developers.

Cross-Entropy Guided Routing in Mixture-of-Experts Large Language Models

arXiv:2609.37751v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) large language models scale model capacity by routing each token to a small subset of experts. Their routers are regular

CruxBench: A Benchmark of Information Discovery

arXiv:2609.35879v1 Announce Type: cross Abstract: Benchmarks for large language models (LLMs) typically evaluate the accuracy of answers against fixed reference labels. But a central step in many comp

CypherTurn: A Multi-Turn Benchmark for Conversational Text-to-Cypher Evaluation and the Autonomy Divergence

arXiv:2609.36987v1 Announce Type: new Abstract: Graph databases are increasingly queried through natural language, yet every existing benchmark evaluates isolated single-turn queries rather than the m

Dagger: Decoupling-based Model Stealing Attack against Graph Neural Networks

arXiv:2609.37972v1 Announce Type: cross Abstract: As Graph Neural Networks (GNNs) are widely deployed as Machine Learning-as-a-Service (MLaaS) APIs, model stealing attacks have emerged as a critical s

Data Agent Kit is now GA: Bring Google Data Cloud to any coding agent

model-releasesgoogle-cloud-ai

Today, Google Cloud Data Agent Kit is generally available. Data Agent Kit is a free set of Model Context Protocol (MCP) tools and agent skills that lets the coding agent you already use work directly

Data centers on the ground are limited by permits and power. SpaceX's answer is Starmind, orbital AI data centers with about 72 Nvidia chips…

model-releaseselon-musk--x

Data centers on the ground are limited by permits and power. SpaceX's answer is Starmind, orbital AI data centers with about 72 Nvidia chips and up to 175 kW per satellite. That's about 5,700 satellit

Data-Free Pruning of Self-Attention Layers in LLMs

arXiv:2512.20636v2 Announce Type: replace-cross Abstract: Many self-attention sublayers in large language models (LLMs) can be removed with little to no loss. We attribute this to the Attention Suppre

DatalogBench: Evaluating Large Language Models on Text-to-Datalog Synthesis

arXiv:2609.37233v1 Announce Type: cross Abstract: Datalog underpins reasoning tasks such as program analysis, but its programs are hard to write. Existing synthesizers automate this task but require u