Search: “persistence”

What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification

arXiv:2609.38420v1 Announce Type: cross Abstract: We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the infer

1 Oct 2026

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Model Releases

When a Kindergartener Solves Calculus: Measuring Capability Leakage in Role-Prompted Reasoning Models

DGX agent

arXiv:2609.39846v1 Announce Type: cross Abstract: We investigate the problem of role-capability leakage (RCL), in which a role-prompted reasoning model generates convincing in-role text while continui

model-releasesarxiv-cs-ai

1 Oct 2026

When Clipping Reverses Correction: Failure Dynamics of Pointwise Forward-KL On-Policy Self-Distillation

arXiv:2609.38995v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own generated responses using feedback from the same model conditioned on privileged informat

safetyarxiv-cs-cl

1 Oct 2026

When the Right Answer Is Missing: An Arithmetic-Dependent Rejection Bottleneck in Jev

arXiv:2609.39496v1 Announce Type: cross Abstract: Typed decision models such as Jev offer an efficient alternative to generative LLMs in decision-making workflows by selecting directly from predefined

researcharxiv-cs-cl

1 Oct 2026

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

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

AnyAct: Universal Action for Self-Evolving Agents

arXiv:2609.37025v1 Announce Type: new Abstract: As large language models (LLMs) advance, AI agents are increasingly deployed in open-world environments to tackle complex sequential tasks (e.g., docume

ARK: A Dual-Axis Multimodal Retrieval Benchmark along Reasoning and Knowledge

model-releasesarxiv-cs-cv

arXiv:2602.09839v2 Announce Type: replace Abstract: Existing multimodal retrieval benchmarks largely emphasize semantic matching on daily-life images and offer limited diagnostics of professional know

Asking for What Was Never Requested: Horizontal and Vertical Proactivity in Agents

arXiv:2609.37236v1 Announce Type: new Abstract: An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested.

Backdoor in the Loop: Compromising Agentic Search via Malicious Retrievers

arXiv:2609.37468v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves reasoning with repeated retrieval, giving the retriever influence over both the evidence an a

agentsarxiv-cs-ai

Beyond Lip Sync: Reference-Grounded Oral Refinement for Audio-Driven Portrait Animation

model-releasesarxiv-cs-cv

arXiv:2609.38019v1 Announce Type: new Abstract: We present RGOR (Reference-Grounded Oral Refinement), an audio-driven lip-sync framework that renders the mouth of the specific person being dubbed rath

Beyond Readability: Evaluating Task Information Recoverability

arXiv:2609.36957v1 Announce Type: new Abstract: Direct visual readability and task-information recoverability are different quantities. Failure to decode a target from a fixed observation need not eli

researcharxiv-cs-cv

Can Representation Learning Decouple from Loss Minimization? Polar Updates Have an Answer

arXiv:2609.36240v1 Announce Type: new Abstract: Does representation learning stop when the training loss stops improving? We study this question for matrix Muon, whose polar-normalised updates have a

safetyarxiv-cs-lg

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

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

Cross-Organizational SysML Model Integration: A Survey of Challenges and AI-Supported Tasks

arXiv:2609.37000v1 Announce Type: cross Abstract: Cross-organizational collaboration is widely regarded as a key promise of SysML-based Model-Based Systems Engineering (MBSE), yet practitioners still

safetyarxiv-cs-ai

Local Ai

CrossTimeEdit: A Decade-Spanning Cross-View Dataset and Reward-Guided Editing for Historical Street-View Generation

arXiv:2609.36616v1 Announce Type: new Abstract: Historical street-view imagery records urban evolution, but uneven coverage leaves substantial gaps in historical records. Generating plausible past app

local-aiarxiv-cs-cv

Distilling Agentic Systems: A Roadmap across Models, Artifacts, and Harnesses

arXiv:2609.36630v1 Announce Type: new Abstract: Modern agents increasingly rely on memories, tools, and execution logic, so their competence extends beyond model parameters. This shift exposes a limit

agentsarxiv-cs-ai

Does Local Video Understanding Transfer Across Encounters? The EgoGears Benchmark

arXiv:2609.37938v1 Announce Type: cross Abstract: Embodied systems must make knowledge acquired during one encounter usable in another despite changes in viewpoint, motion, and illumination. Yet aggre

Early Learning Shapes Later Directions Of Representation Change In Continual Learning

arXiv:2609.36081v1 Announce Type: new Abstract: Representations continually change as a network learns new tasks. We ask whether early representational changes naturally form a geometric structure tha

researcharxiv-cs-lg

EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory

arXiv:2609.37923v1 Announce Type: new Abstract: Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce Ep

agentsarxiv-cs-cv

Equally Good, Yet Different: Benchmarking Rashomon sets in AutoML packages

model-releasesarxiv-cs-lg

arXiv:2609.36970v1 Announce Type: new Abstract: The Rashomon effect describes the existence of multiple near-optimal models that achieve comparable performance while offering fundamentally different e

From Learner Behavior to Reusable Skills for Effective and Efficient Learner Simulation

arXiv:2609.37157v1 Announce Type: new Abstract: Learner simulation aims to reproduce how a particular learner behaves on new tasks. Although Large Language Models (LLMs) can generate increasingly fine

Frontier Autolab: Organizational Memory, Adversarial Dissent and Temporal Leakage in Multi-Agent LLM Firms Across Fifty Years of Technological Change

arXiv:2609.36739v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly structured like organizations, with roles, critics and shared memory, yet they are evaluated on tasks that la

Generated Query Expansion Still Helps Strong Sparse Retrieval: A Controlled Study with SPLADE-v3

arXiv:2609.37911v1 Announce Type: cross Abstract: Scientific queries are often brief, while relevant papers use specialized vocabulary. Generated query expansion can bridge this mismatch, but earlier

GNA: Granular Neighbor Assembly for Retrieval-Augmented Multivariate Time-Series Forecasting

arXiv:2609.36281v1 Announce Type: new Abstract: Deep forecasters predict from a fixed-length lookback window, and lengthening it gives diminishing returns at a growing cost. Retrieval augmentation ins

researcharxiv-cs-lg

Godel Forest: Balancing Search Depth and Breadth for Data-Centric Recursive Self-Improvement

arXiv:2609.36675v1 Announce Type: new Abstract: Recursive self-improvement (RSI) aims to achieve compounding gains by having models improve themselves. While most existing RSI systems optimize externa

agentsarxiv-cs-cl

HeadGuard: Selective Head Protection for Low-Bit VLM KV-Cache Quantization

model-releasesarxiv-cs-cv

arXiv:2609.35800v1 Announce Type: cross Abstract: Low-bit key-value (KV) cache quantization saves storage but can sharply degrade vision-language model (VLM) accuracy. We introduce HeadGuard, a compos

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

researcharxiv-cs-lg

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

Improving Function Space Flow Matching with Kernel Optimal Transport

model-releasesarxiv-cs-lg

arXiv:2609.38049v1 Announce Type: new Abstract: Generative models for function-valued data, such as time series and solutions of partial differential equations, must learn distributions over infinite-

Introducing the CZAR Loss: A Tailored Objective Function for Financial Log-Return Predictions

arXiv:2609.36061v1 Announce Type: new Abstract: In quantitative finance, standard regression losses are misaligned with the economics of return prediction. As the conditional mean of financial log-ret

safetyarxiv-cs-lg

LongSpark: Efficient speculative decoding with a fixed-cost parallel drafter

arXiv:2609.37029v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive inference by verifying multiple draft tokens in a single target forward pass. However, as the context

Tutorials

Non-negative Matrix Factorisation with Topological Regularisation

arXiv:2606.17531v2 Announce Type: replace Abstract: Non-negative matrix factorisation (NMF) learns additive representations from data, but non-negativity alone does not ensure interpretable basis func

tutorialsarxiv-cs-lg

Tutorials

Passive-Dynamic-Walking-Inspired Dynamics Guidance for Energy-Efficient Humanoid Locomotion

arXiv:2609.35935v1 Announce Type: new Abstract: Learning energy-efficient humanoid locomotion requires discovering mechanically economical gait coordination, not merely reducing actuator effort. Reinf

tutorialsarxiv-cs-ro

PDE-OBS: Controlled Evaluation Across Observation Patterns

model-releasesarxiv-cs-lg

arXiv:2609.36521v2 Announce Type: new Abstract: Physical-field reconstruction and forecasting depend on both measurement density and spatial layout, yet evaluation under a single observation pattern d

Pruning for Efficiency, Paying in Fairness: Demographic Disparities in Pruned Speech-LLMs

arXiv:2609.38106v1 Announce Type: cross Abstract: Speech-LLMs are expensive to run, making compression important for real-world deployment. However, compressed models are usually selected using aggreg

safetyarxiv-cs-cl

REALHOP: Rethinking Multi-Hop Reasoning Evaluation via Behavioral Auditing

arXiv:2609.36984v1 Announce Type: new Abstract: Complex questions often require multi-hop reasoning that connects facts distributed across sources or distant regions of a long context through intermed

ReF-HIL: Shaping the Critic around Human Action Neighborhoods for Efficient Human-in-the-Loop Reinforcement Learning

arXiv:2609.37131v1 Announce Type: new Abstract: Human-in-the-loop reinforcement learning (HIL-RL) offers a promising route to efficient training of robotic manipulation policies by combining autonomou

safetyarxiv-cs-ro

Tutorials

ReWorld-Track: A Recursive Event World Model for Language-Guided Multi-Camera Tracking

arXiv:2609.36677v1 Announce Type: new Abstract: Language-guided multi-camera tracking must preserve a target identity across unobserved gaps, where similar candidates and uncertain returns can make ea

tutorialsarxiv-cs-cv

S4VY: Segment Anything in Feed-Forward 4D Visual Geometry

arXiv:2609.36875v1 Announce Type: new Abstract: Accurate instance segmentation in dynamic scenes is important for downstream applications such as robotics and autonomous driving. Existing Segment Anyt

agentsarxiv-cs-cv

SAKI: Skill Assembly and Kinematic Imitation from Human Videos for Long-Horizon Mobile Manipulation

arXiv:2609.36031v1 Announce Type: new Abstract: Learning from human videos offers a promising route to acquiring diverse manipulation skills. Extending this capability beyond tabletop settings to long

researcharxiv-cs-ro

Same Bytes, Different Authority: Reserved-Token Representations in Chat-Template Prompt Injection

arXiv:2609.35932v1 Announce Type: cross Abstract: Prompt injection against LLM agents becomes much stronger when the injected instruction is wrapped in the model's own chat template. A forged template

Seeing Is Not Addressing: Auditing Linguistic Access to Frozen Visual Geometry

arXiv:2609.37230v1 Announce Type: new Abstract: Visual distinctions are often finer than those reflected in linguistic conceptualization. Vision-language models exhibit a similar asymmetry: a distinct

safetyarxiv-cs-cv

Simple Agentic Memory for Generalist Robot Policies

arXiv:2609.36595v1 Announce Type: cross Abstract: Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual

Hardware

So I would like to share my analysis of PD disagg that I've run by Horace and many folks at Thinky You may have heard that PD disagg helps w…

hardwaresoumith-chintala--x

So I would like to share my analysis of PD disagg that I've run by Horace and many folks at Thinky You may have heard that PD disagg helps with per-token 'tail latencies' in ITL/TPOT, as prefill inter

Socialality Anchors: Towards Group-bounded Trajectory Prediction

arXiv:2609.36852v1 Announce Type: new Abstract: Trajectory prediction is a key component for understanding human behavior patterns in dynamic scenes. Researchers have devoted substantial efforts to mo

agentsarxiv-cs-cv

Solver Agent: an Agentic AI Framework for Theoretical Physics Computations Applied to F-theory Uplifts of O3-planes and S-folds

arXiv:2609.35958v1 Announce Type: cross Abstract: We introduce Solver Agent, an AI framework based on large language models for calculations and proofs in mathematics and theoretical physics. The solu

agentsarxiv-cs-ai