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A foundation model for energy and radiation systems built on heterogeneous scientific interfaces

model-releasesarxiv-cs-lg

arXiv:2609.38067v1 Announce Type: new Abstract: Scientific foundation models are commonly evaluated after heterogeneous physical problems have already been translated into a compatible gridded, tokeni

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Research

A Mesoscopic View of Transformer Weights Through Row and Column Scale Fields

DGX agent

arXiv:2609.35852v1 Announce Type: new Abstract: Pooled statistics of Transformer weights obscure how magnitude is distributed across functional channels, while individual weights are too numerous to c

researcharxiv-cs-lg

30 Sept 2026

A Model-Agnostic Physics-Guided Adapter for Few-Shot Transfer of Coastal Flood Prediction Models to Unseen Regions

model-releasesarxiv-cs-lg

arXiv:2609.37565v1 Announce Type: new Abstract: Deep learning surrogates can produce high-resolution coastal flood maps orders of magnitude faster than physics-based hydrodynamic simulators, yet trans

A neural network that maintains and retrieves memories based on context

arXiv:2609.37791v1 Announce Type: new Abstract: Every day, people continuously infer situational context and adjust the way they understand and remember the world. Context, signaled by the prefrontal

A Polyphonic Conception of AI Understanding

arXiv:2609.36079v1 Announce Type: new Abstract: When a doctor, a judge, or an engineer must decide whether to trust an AI model's output, they cannot avoid asking what the model understands. Purely ma

local-aiarxiv-cs-ai

A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses

arXiv:2609.37788v1 Announce Type: cross Abstract: Rubrics support the structured evaluation of language models. We propose a rubric for assessing expressed clinical reasoning in model responses, drawi

safetyarxiv-cs-ai

Applications

A QCQP-Representable IMU Pre-Integration Factor for Certifiable State Estimation

arXiv:2609.38048v1 Announce Type: new Abstract: We propose a QCQP-representable IMU pre-integration factor that enables certifiable estimation with pre-integrated inertial measurements. To the best of

applicationsarxiv-cs-ro

A robust single-sensing-element tactile sensor for concurrent pressure and tackiness detection with real-time signal decoupling capability

arXiv:2609.36558v1 Announce Type: new Abstract: Integrating tackiness sensation into the artificial skin of humanoid robots significantly enhances their cognitive and operational capabilities. However

researcharxiv-cs-ro

A Sharp Transition in Data Reconstruction under Differential Privacy

arXiv:2609.37344v1 Announce Type: cross Abstract: Data reconstruction attacks have empirically been successful in recovering training samples from learned models, raising privacy concerns and motivati

A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding

model-releasesarxiv-cs-cv

arXiv:2603.14733v2 Announce Type: replace Abstract: Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos

A Spectral Theory of Distortion in LLM Graph Reconstruction: Sharp Bounds and Empirical Characterization

arXiv:2609.38161v1 Announce Type: new Abstract: Evaluations of graph reconstruction by language models typically report a single aggregate distance between the original and the reconstructed graph. We

safetyarxiv-cs-lg

A theoretical model of dynamical grammatical gender shifting based on set-valued set function

arXiv:2603.03510v3 Announce Type: replace-cross Abstract: This study investigates the diverse characteristics of nouns, focusing on both semantic (e.g., countable/uncountable) and morphosyntactic (e.g

Agents

A thing to know about the AI business is labs that have frontier models can release half-built products and they work surprisingly well beca…

A thing to know about the AI business is labs that have frontier models can release half-built products and they work surprisingly well because the AI can just figure stuff out and improvise. Its like

agentsethan-mollick--x

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

Abductive World Modeling via Causal Representation Learning

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

Agents

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

agentsarxiv-cs-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

Agents

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

agentsarxiv-cs-ai

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

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

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 a brief period where OpenAI seemed to be unifying work around the ChatGPT app, between Dot and Spaces and Pages and local/cloud ChatGP…

After a brief period where OpenAI seemed to be unifying work around the ChatGPT app, between Dot and Spaces and Pages and local/cloud ChatGPT Work and Scheduled Tasks in the Cloud and Scheduled Tasks

local-aiethan-mollick--x