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ABC: Advantage-Based Control Variates for Reinforcement Learning with Verifiable Rewards

arXiv:2609.36058v1 Announce Type: new Abstract: Recent progress in reinforcement learning with verifiable rewards (RLVR) has highlighted the effectiveness of simple critic-free policy-gradient methods

safetyarxiv-cs-lg

Tutorials

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Abductive World Modeling via Causal Representation Learning

DGX agent

arXiv:2609.36985v1 Announce Type: cross Abstract: The central challenge of world modeling is to learn representations that capture how the world evolves. However, existing world models predominantly r

tutorialsarxiv-cs-ai

30 Sept 2026

Absorbed in Inertia: Activation Analysis for Computer-Use Agents

arXiv:2609.37176v1 Announce Type: new Abstract: Computer-use agents have become increasingly capable of executing tasks on live desktops through natural-language instructions, based on trajectories of

Local Ai

Accelerated surrogate dynamics for dynamical, stochastic system evolution

arXiv:2609.37184v1 Announce Type: new Abstract: Dynamic simulations are an entrenched way of gaining insight into the evolution of system dynamics. Their computational cost however is often prohibitiv

local-aiarxiv-cs-ai

Accessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding Access

arXiv:2609.36129v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expa

Achieving an O(1/N) Optimality Gap in Average-Reward Weakly-Coupled MDPs

arXiv:2609.38132v1 Announce Type: new Abstract: We study average-reward weakly-coupled Markov decision processes (WCMDPs), where a WCMDP consists of N smaller MDPs, called arms, that share multiple pe

safetyarxiv-cs-lg

Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation

arXiv:2508.17171v3 Announce Type: replace Abstract: Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibr

researcharxiv-cs-cv

Act First, Reason Later: Accelerating On-Policy Distillation for Multi-Turn Agents via Reference-Conditioned Inverse Dynamics

model-releasesarxiv-cs-cl

arXiv:2609.36608v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains multi-turn language agents with dense teacher supervision on student-generated responses. However, standard think-

Action Chunking Proximal Policy Optimization with Feedback Correction

arXiv:2609.36250v1 Announce Type: cross Abstract: Action chunking provides temporal abstraction in reinforcement learning by selecting short action sequences instead of individual actions, but many ex

safetyarxiv-cs-ro

Active Budget Can Kill Sensitivity: Diagnosing and Repairing TopK Sparse Autoencoder Reliability

arXiv:2609.37857v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly scaled to wider dictionaries to recover fine-grained structure from large language model activations. Howeve

researcharxiv-cs-ai

ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3

arXiv:2606.16996v2 Announce Type: replace-cross Abstract: Segment Anything Model 3 (SAM 3) provides a strong frozen backbone for concept-prompted segmentation, but applying it directly to open-vocabul

actr: aligning thoughts and responses for multilingual safety in reasoning llms

arXiv:2609.37054v1 Announce Type: new Abstract: Ensuring the safety of reasoning large language models (LLMs) across languages is essential for their reliable deployment. However, when exposed to jail

safetyarxiv-cs-ai

AdaKerNet: Neural Kernel Decoding for Task-Adaptive Prediction with Multimodal Large Models

arXiv:2609.36368v1 Announce Type: cross Abstract: Large foundation models have been introduced with the promise of efficient adaptation to downstream tasks. Yet, under limited supervision, MLLMs, an i

Adam under Generalized Smoothness with Second-Moment-Type Stochastic Gradients

arXiv:2609.37787v1 Announce Type: new Abstract: Adam is widely observed to remain stable even when the objective deviates significantly from global smoothness. Under the generalized smoothness framewo

researcharxiv-cs-ai

AdaptArena: Evaluating Test-Time Personalization of Web Agents

model-releasesarxiv-cs-lg

arXiv:2609.36488v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings w

Adapting Context Compression for Long-Horizon Agents with Counterfactual Continuations

arXiv:2609.36526v1 Announce Type: cross Abstract: Long-horizon agents require context compression to manage growing interaction histories. Compression quality, however, is ultimately determined by dow

Adapting Linear-Time Architectures for Tabular In-Context Learning

arXiv:2609.36337v1 Announce Type: new Abstract: Tabular foundation models achieve strong performance by conditioning on labelled examples in context, but softmax attention limits their use on large da

researcharxiv-cs-lg

Adaptive Consistency Graph for Long-Horizon Agents

arXiv:2609.32754v2 Announce Type: replace Abstract: Large language model agents can often make reasonable local decisions on short tasks, yet their performance degrades when success requires long sequ

Local Ai

Adaptive Reward Routing: Dynamic Multi-Reward Optimization for Joint Audio-Video Diffusion via Forward-Process RL

arXiv:2609.37200v1 Announce Type: new Abstract: Multi-reward guided reinforcement learning (i.e., RL) offers a promising way to improve joint audio-video diffusion models along several complementary o

local-aiarxiv-cs-cv

Applications

AdaST: Adaptive Coupling for Spatial-Temporal Forecasting

arXiv:2609.36119v1 Announce Type: new Abstract: Spatial-temporal (ST) forecasting underpins many real-world systems such as traffic, climate, and energy networks. While existing methods implicitly ass

applicationsarxiv-cs-ai

AdaTutoRank: Learning to Rerank Document Sets via Adaptive Tutoring Optimization for RAG and Deep Research

arXiv:2609.32472v2 Announce Type: replace Abstract: Document rerankers determine what evidence reaches the downstream model in RAG and deep research, yet mainstream rerankers select by relevance match

safetyarxiv-cs-cl

ADMM-based Continuous Trajectory Optimization in Graphs of Convex Sets

arXiv:2603.11335v2 Announce Type: replace Abstract: This paper presents a numerical solver for computing continuous trajectories in non-convex environments. Our approach relies on a customized impleme

researcharxiv-cs-ro

AdvancedMathBench: A Benchmark Suite for Advanced Mathematical Proof Generation and Verification

model-releasesarxiv-cs-cl

arXiv:2607.11849v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on high-school and competition-level mathematics, yet their capabilities on advanc

Adversarial Debiasing of Machine Learning Models for Enhanced Network Security against DDoS Attacks

arXiv:2609.36167v1 Announce Type: cross Abstract: Distributed Denial of Service attacks are a growing threat to network infrastructure, and new techniques, including the use of generative AI, make the

Applications

Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation

arXiv:2509.20411v3 Announce Type: replace-cross Abstract: Machine learning-based cybersecurity systems are highly vulnerable to adversarial attacks, while Generative Adversarial Networks (GANs) act as

applicationsarxiv-cs-ai

Adversarial Training for Pixel Diffusion

arXiv:2609.38170v1 Announce Type: new Abstract: Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fi

safetyarxiv-cs-cv

Adversarially Robust Geometric Safety Certificates for Nonholonomic Robots Against Maneuvering Obstacles

arXiv:2609.37126v1 Announce Type: new Abstract: Safe navigation against obstacles that can actively maneuver within bounded capabilities remains challenging: robust control barrier function methods ty

safetyarxiv-cs-ro

AdviSD: Learning to Advise Frontier LLMs via Targeted Multi-Turn Self-Distillation

arXiv:2609.38142v1 Announce Type: new Abstract: A small trainable advisor can steer a frozen language-model executor using natural-language advice. In addition to learning from task rewards, the advis

AdvMT: Adversarial Motion Transformer for Long-term Human Motion Prediction

arXiv:2401.05018v3 Announce Type: replace Abstract: Human motion prediction is a crucial capability for advanced robotic systems that interact with humans. In facilities with dynamic human-robot colla

safetyarxiv-cs-cv

AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search

arXiv:2609.36066v1 Announce Type: cross Abstract: Open-world aerial object-goal search is a foundational yet challenging task, requiring aerial agents to autonomously explore large-scale, unstructured

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations

arXiv:2609.36915v1 Announce Type: cross Abstract: Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities fo

Tutorials

AESOP: Asymmetric Human-Camera Generation with Translation-Intensity Control

arXiv:2609.37229v1 Announce Type: new Abstract: Human motion defines an action, while a camera trajectory determines how it is presented. Camera generation for a given human motion and joint human-cam

tutorialsarxiv-cs-cv

AESplat: Advancing Pose-Free Feed-Forward 3D Gaussian Splatting via Decoupled Appearance Modeling

arXiv:2609.36693v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) has demonstrated remarkable potential for generalized novel view synthesis. However, existing method

researcharxiv-cs-cv

AffectReveal: Event-Grounded Emotion Recognition Beyond Visual Appearances

arXiv:2609.36563v1 Announce Type: new Abstract: Visual emotion recognition commonly assumes that all evidence required for prediction is contained in the observed image or video. Yet the same visible

researcharxiv-cs-cv

After the Fix: Transfer of Corrected Agent Experience

arXiv:2609.34603v2 Announce Type: replace Abstract: Does repairing an episode make its experience a better memory for the next task? We transfer the same failed source before and after accepted repair

AgentBug-Smith: Automatically Reproducing Real-World Harness Bugs in Agentic Systems

arXiv:2609.37864v1 Announce Type: cross Abstract: Agent harness bugs exhibit unique characteristics and remain challenging for state-of-the-art software agents to repair. Progress in this area is furt

Agentic AI for Scalable and Robust Optical Systems Control

arXiv:2602.20144v2 Announce Type: replace-cross Abstract: We present AgentOptics, an agentic AI framework for high-fidelity, autonomous optical system control built on the Model Context Protocol (MCP)

Agentic Commerce Bench: Measuring Fraud Detection for Agents That Spend Money

arXiv:2609.35886v1 Announce Type: cross Abstract: AI agents now hold spend authority and settle payments without per-action human confirmation. The resulting loss is often not a security failure: a co

Agentic Federated Learning: Rule-Based Client and Server Agents for Adaptive Training

arXiv:2609.35914v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it suitable for privacy-sensi

agentsarxiv-cs-lg

Hardware

AI as a Compiler: Compiling Triton kernels without the Triton compiler

arXiv:2609.36800v1 Announce Type: new Abstract: Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language m

hardwarearxiv-cs-ai

Alignment Forecasting: Predicting Misalignment From Training Data

arXiv:2609.35805v1 Announce Type: cross Abstract: Training a language model on data with a narrow flaw can sometimes make the model broadly misaligned. Inspecting the data at face value often does not

All Roads Lead to Rome: Flow-driven Multi-Anchor Exploration for Open-Environment Active 3D Mapping

arXiv:2609.36889v1 Announce Type: new Abstract: To advance the development of embodied intelligence, Open-Environment Active 3D Mapping has attracted increasing attention, aiming to perform a long-hor

researcharxiv-cs-ro

All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control

arXiv:2609.36993v1 Announce Type: new Abstract: Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fis

safetyarxiv-cs-ro

Almost Human, Except When It Matters: VoxParity and the Decisions a Voice Should Change

arXiv:2609.35922v1 Announce Type: cross Abstract: A voice agent can handle almost every call on the words alone and still fail the few its sector's rules were written for. Emergency-call standards, fr

Alpha Diffusion Language Models: Factorization Alone Is Not the Problem

arXiv:2609.38066v1 Announce Type: new Abstract: Discrete diffusion language models can generate multiple tokens in parallel, but reducing the number of denoising steps can lead to inconsistent predict

researcharxiv-cs-lg

Altered Thoughts, Altered Actions: Reasoning Chain as Control Surface for a Vision-Language-Action Policy

arXiv:2603.12717v2 Announce Type: replace-cross Abstract: Vision-language-action policies map camera images and natural-language instructions to a robot's motor actions. Some of these policies are des

safetyarxiv-cs-ai

Tutorials

Amadeus: When Models of People Meet

arXiv:2609.35835v1 Announce Type: cross Abstract: With the sheer constant advancements raining down in the field of Artificial Intelligence, one particular possibility that may cross our mind is wheth

tutorialsarxiv-cs-lg

AMU:Admission and Memory Update for Personalized Conversations---Structured Memory with SLM Guided Control

arXiv:2609.36976v1 Announce Type: new Abstract: Large language models (LLMs) have become the foundation of personalized assistants, but maintaining persistent user memory across long-term interactions

researcharxiv-cs-cl