All entries

OdysSim: Building Foundation Models for Human Behavior Simulation

arXiv:2606.14199v2 Announce Type: replace-cross Abstract: Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven p

Omni Interaction Agent Technical Report

Content type

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DGX agent

arXiv:2609.08977v1 Announce Type: cross Abstract: In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction, and agentic capabilities within a single fram

agentsarxiv-cs-lg

9 Sept 2026

OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments

arXiv:2609.08159v1 Announce Type: new Abstract: Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requi

applicationsarxiv-cs-ro

On BatchNorm Forward Modes in Value-Based Reinforcement Learning

arXiv:2609.06421v1 Announce Type: new Abstract: Batch normalization (BN) substantially improves sample efficiency in continuous-control actor-critic methods such as CrossQ, yet recent studies report p

On Generalisation Error Bounds for Transformers

arXiv:2410.11500v2 Announce Type: replace-cross Abstract: In this paper, we establish a collection of covering number bounds for linear function classes under various norm constraints on the inputs an

On the Effectiveness of the z-Transform Method in Quadratic Optimization

arXiv:2507.03404v3 Announce Type: replace Abstract: The z-transform of a sequence is a classical tool used within signal processing, control theory, computer science, and electrical engineering. It al

On the flip slide there is a >10% chance that AI could save all humans by curing disease and aging in the next decade

On the flip slide there is a >10% chance that AI could save all humans by curing disease and aging in the next decade Jacob is correct here—we really do earnestly believe AI could kill all humans! I p

safetyemad-mostaque--x

On-the-go Forgetting without Explicit Unlearning via ERASE

arXiv:2609.05966v1 Announce Type: new Abstract: Existing unlearning approaches typically rely on post hoc weight adaptation or distillation, leading to duplicated memory costs, degraded generalization

On the Potential of Graph Neural Networks as Metamodels for Supply Chain Optimization: Dataset, Architectures, and Directions

arXiv:2607.16769v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have emerged as a powerful, differentiable class of learning models for graph-structured systems. Their ability to gene

On the Recall Scaling Laws in Mamba: A Theoretical and Mechanistic Study via Hashing

arXiv:2609.07681v1 Announce Type: new Abstract: Associative Recall (AR) is the cognitive ability to learn and retrieve links between items in memory. In NLP, AR is used as a benchmark for evaluating t

ONE CYLinder: A Benchmark for Graph-Based Surrogate Modeling of Unsteady Bluff-Body Flows

arXiv:2609.08947v1 Announce Type: cross Abstract: Graph-based surrogate models offer a promising route to accelerate computational fluid dynamics (CFD) simulations on unstructured meshes. However, the

One for All: Generalist Foundation Model for Cross-Sensor Skeleton Representation Learning

arXiv:2609.07078v1 Announce Type: new Abstract: For learning generalizable motion representations from large-scale unlabeled data, Self-supervised learning (SSL) has become a widely adopted methodolog

researcharxiv-cs-cv

One MLLM, One Call: Efficient Zero-Shot Vision-and-Language Navigation via Spatial-Aware Waypoints

arXiv:2609.06476v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate unseen environments by following natural langu

agentsarxiv-cs-cv

One Model, Two Worlds: Bidirectional Sonar-Optical Translation

arXiv:2609.06253v1 Announce Type: new Abstract: Translating between imaging sonar and optical cameras is valuable for underwater perception, but supporting both directions with separate models duplica

researcharxiv-cs-cv

One Perturbation Is Not Enough: Identifiability and Blind Baselines for Behavioral AI Evaluation

arXiv:2609.06190v1 Announce Type: new Abstract: Behavioral evaluations perturb an input and read the induced change in the output in order to certify that a system uses that input. We show that the nu

safetyarxiv-cs-cv

One Rate Is Not Enough: Adaptive Anisotropic Learning Rates for LoRA Fine-Tuning

arXiv:2609.05885v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has become the standard for parameter-efficient fine-tuning of large language models. Most LoRA variants follow a uniform-LR

One Shared LoRA Weight for MRI Reconstruction across Acceleration Factors

model-releasesarxiv-cs-cv

arXiv:2609.06338v1 Announce Type: new Abstract: Accelerated MRI reconstruction recovers images from undersampled k-space. However, different acceleration factors produce distinct artifact patterns. Ex

One Step, One Lead: Mitigating Higher-Order Interference in Multi-Domain Reinforcement Learning via Cross-Step Control

arXiv:2609.06469v1 Announce Type: new Abstract: Reinforcement learning (RL) across multiple domains can broaden the reasoning capabilities of large language models (LLMs), yet joint training often deg

safetyarxiv-cs-lg

Local Ai

Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training

arXiv:2609.07108v1 Announce Type: new Abstract: Speculative decoding accelerates rollout generation, which dominates the cost of reinforcement learning (RL) post-training. Online co-training can furth

local-aiarxiv-cs-lg

Tutorials

Online Learning with LLM Experts from Limited Feedback

arXiv:2609.05820v1 Announce Type: new Abstract: We study adaptive routing of prompts to large language model (LLM) experts to maximize response quality in an online setting with limited feedback. We f

tutorialsarxiv-cs-lg

Online, Reachability-Aware, Sampling-Based Motion Planning

arXiv:2609.09073v1 Announce Type: new Abstract: Sampling-Based Model-Predictive Control (MPC) algorithms are a flexible class of controllers used for navigation on a wide range of robotic systems. His

safetyarxiv-cs-ro

Online Signature Verification Using Augmented Path Signature and T-Mamba

model-releasesarxiv-cs-cv

arXiv:2609.08276v1 Announce Type: cross Abstract: Handwritten signature verification is vital for personal authentication across commercial and financial applications. Although deep learning methods a

Online Surrogate Repair: Decoupling High-Fidelity Feedback from Search Length in Closed-Loop Discovery

arXiv:2609.07655v1 Announce Type: new Abstract: Closed-loop AI scientists can generate candidate designs at low marginal computational cost, whereas reliable feedback may require wet-lab synthesis, ch

agentsarxiv-cs-lg

Tutorials

Open hardware from @huggingface (https://huggingface.co/docs/lerobot/en/so101) + frontier AI = 🔥🔥🔥

tutorialsclem-delangue--x

Open hardware from @huggingface (https://huggingface.co/docs/lerobot/en/so101) + frontier AI = 🔥🔥🔥 i gave astra a robot, a paint brush, and a camera then asked it to paint the golden gate bridge in re

Open-Set Ego-Noise Separation for Legged-Robot Audition via Annotation-Free Adaptation and Pretrained-Model Transfer

arXiv:2609.07440v1 Announce Type: new Abstract: This paper proposes an open-set ego-noise separation framework for legged-robot audition via annotation-free adaptation and pretrained-model transfer. T

researcharxiv-cs-ro

OpenAI is looking more and more like a clownshow.

OpenAI is looking more and more like a clownshow. OpenAI’s rogue AI agents reached at least 12 more websites, researchers say https://fortune.com/2026/09/09/openai-rogue-ai-agents-reached-12-more-webs

safetygary-marcus--x

Industry

OpenAI says it is working with Samsung on its next-gen chips, and Samsung is one of the 'largest-scale deployments of ChatGPT globally' (Heekyong Yang/Reuters)

Heekyong Yang / Reuters: OpenAI says it is working with Samsung on its next-gen chips, and Samsung is one of the “largest-scale deployments of ChatGPT globally” — OpenAI is deepening cooperation with

industrytechmeme

Industry

OpenAI’s ChatGPT Images gets faster, with sharper details and more refined edits

OpenAI Group PBC said today it’s giving its image-generation tool a bit more artistic flair, announcing the launch of ChatGPT Images 2.5, an update to ChatGPT Images 2.0 that debuted in April. Accordi

industrysiliconangle

OpenAI’s rogue AI agents reached at least 12 more websites, researchers say https://fortune.com/2026/09/09/openai-rogue-ai-agents-reached-12…

Researchers reported in September 2026 that OpenAI’s rogue AI agents accessed at least twelve additional online sites, including university servers, Wikipedia, and text‑sharing platforms. These sites

safetygary-marcus--x

Industry

OpenAI’s sly mathematical breakthrough sends a chill through academia

OpenAI's announcement Tuesday that it has solved one of mathematics' legendary Millennium Prize problems should have been a moment of triumph. The result is both an undeniable achievement and a striki

industrythe-verge-ai

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

arXiv:2609.07398v1 Announce Type: new Abstract: World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Ex

applicationsarxiv-cs-ro

Optimal estimation for Functional Linear Regression with Noisy Discretized Data

arXiv:2609.08671v1 Announce Type: cross Abstract: In this paper, we consider the scalar-on-function linear regression model under a realistic sampling scheme in which the functional covariates are obs

Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling

arXiv:2609.08172v1 Announce Type: cross Abstract: Slice sampling is a Markov chain Monte Carlo algorithm that draws its next state uniformly from a 'slice'---a super-level set of the target density fu

OracleZoom: On-Policy Self-Distillation Inspired Reference-Constrained Recursive Image Super Resolution

arXiv:2609.06490v1 Announce Type: new Abstract: Recursive Super-Resolution (SR) extends fixed-scale SR to extreme magnification by repeatedly feeding predictions back into the same model, analogous to

safetyarxiv-cs-cv

Orchid Security gives enterprises a kill switch for rogue AI agents

Identity security startup Orchid Security Inc. today added identity drift detection and application-level kill switches for artificial intelligence agents to its Identity Control Plane. The controls a

agentssiliconangle

Organization of Valence and Arousal in Vision-Language Representations of Built Environments: Insights from the EMOIS Dataset

model-releasesarxiv-cs-cv

arXiv:2609.06870v1 Announce Type: new Abstract: Visual perception of built environments contributes to the affective impressions that people form in everyday life. However, how these impressions are r

Hardware

Ostrich: Taking Large Strides Through Stiff Contact in Differentiable Dynamics

arXiv:2609.08800v1 Announce Type: cross Abstract: Three properties determine whether a differentiable simulator can drive gradient-based optimization through contact: simulation accuracy, gradient rel

hardwarearxiv-cs-lg

Our agentic extraction harness can extract 54+ fields from an insurance policy with 100% accuracy ✅ coverage limits ✅ nested sublimits ✅ exp…

Our agentic extraction harness can extract 54+ fields from an insurance policy with 100% accuracy ✅ coverage limits ✅ nested sublimits ✅ explicit noncoverage This includes a full result review UI wher

safetyjerry-liu--x

OVMAN: A Task and Benchmark for Open-Vocabulary Motion-Aware Navigation

model-releasesarxiv-cs-ro

arXiv:2609.06424v1 Announce Type: new Abstract: Homes change between a robot's visits. Navigation benchmarks pose their goals in the world the agent currently sees, and the two-visit benchmarks that e

P^2Calib: Utilizing Pattern Priors for LiDAR-Camera Extrinsic Calibration

model-releasesarxiv-cs-ro

arXiv:2609.07516v1 Announce Type: new Abstract: Target-based LiDAR-camera extrinsic calibration is a prerequisite for multi-sensor fusion in robotics. However, in the widely adopted four-hole pipeline

PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise

arXiv:2609.08740v1 Announce Type: new Abstract: In this paper we derive a Probably Approximately Correct (PAC)-Bayesian error bound for partially observed linear time-invariant (LTI) stochastic dynami

PAC-Private Autoregressive Generation: Calibrating Noise to Ensemble Disagreement

arXiv:2609.05676v1 Announce Type: new Abstract: Language models adapted on private text are often served through APIs, so privacy leakage occurs through generated outputs rather than exposed weights.

PAI-Actor: Cinematic Multi-Character Replacement in Dynamic Scenes

arXiv:2609.05918v1 Announce Type: new Abstract: We present PAI-Actor, a cinematic multi-character animation framework for character replacement in dynamic movie scenes. Unlike conventional animation s

applicationsarxiv-cs-cv

PAN: A World Model for General, Actionable, and Long-Horizon World Simulation

arXiv:2511.09057v4 Announce Type: replace Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spont

applicationsarxiv-cs-cv

Parallelism Strategy Chaining for Fast Training Convergence

arXiv:2609.07236v1 Announce Type: new Abstract: Selecting a parallelism strategy - the configuration of data, tensor, and pipeline parallelism degrees together with micro- and global-batch sizes - lar

Parameterized and Streaming Algorithms for Euclidean Fair k-Center Clustering

arXiv:2609.06384v1 Announce Type: new Abstract: Motivated by the growing importance of fairness in machine learning, fair k-center clustering has attracted considerable research attention as a fundame

safetyarxiv-cs-lg

Tutorials

ParetoTransport: Generative Optimization by Mass Transport Toward The Pareto Front

arXiv:2609.07706v1 Announce Type: new Abstract: Offline multi-objective optimization requires not only moving the objective vectors of candidate designs toward the Pareto front, but also distributing

tutorialsarxiv-cs-lg

Parity, Sensitivity, and Transformers

arXiv:2602.05896v3 Announce Type: replace Abstract: Understanding what neural architectures can and cannot compute is a central challenge in the theory of AI. One of the fundamental problems in this c