Search: “inference”

Evaluating Persistent Calibration under Evolving Model Knowledge

arXiv:2609.38797v1 Announce Type: cross Abstract: As AI systems move from static repositories to agents that are capable of continual adaptation and learning, maintaining their trustworthiness means e

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ExploreNet: Learning Where to Explore in Diffusion GRPO

DGX agent

arXiv:2609.38329v1 Announce Type: new Abstract: Group-relative RL methods such as Flow-GRPO post-train image generators by exploring with isotropic Gaussian noise added at every denoising step. This n

safetyarxiv-cs-cv

1 Oct 2026

FORTE: Forecasting Occupancy for Spatiotemporal Risk-Aware Planning in Dynamic Environments

arXiv:2609.39305v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires anticipating future environmental states to account for spatiotemporal risks, specifically when and whe

researcharxiv-cs-ro

FrameMorrow: Future-guided Frame Selection with Prospective Tokens for Long-Horizon Video Generation

arXiv:2609.38839v1 Announce Type: new Abstract: Long-horizon video generation requires models to effectively leverage an increasingly long generation history. As the generated history grows, retaining

safetyarxiv-cs-cv

Function-Space Transformer with Adaptive Anchors

arXiv:2609.38348v1 Announce Type: new Abstract: Many forms of data, including physical fields, geometric shapes, and visual signals, are naturally described by functions over continuous domains but ar

Geometry-physics confounding impairs PDE learning across varying domains

arXiv:2609.38623v1 Announce Type: new Abstract: Learning partial differential equation (PDE) dynamics across varying domains is central to predictive modelling and data-driven discovery of governing e

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

hardwarearxiv-cs-lg

Ghost in the Encoder: Decodable Artist Identity Representations in Lyrics-to-Song Generation

arXiv:2609.39552v1 Announce Type: cross Abstract: Text-to-song generation models can be prompted to imitate specific artists or regurgitate entire songs from their training data. Although these phenom

applicationsarxiv-cs-lg

GrammarRL: Effective Grammar-Constrained Decoding via Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2609.39869v1 Announce Type: new Abstract: Grammar-constrained generation guarantees syntactic validity, but can substantially degrade semantic quality when the model's preferred outputs are poor

GraphToxin: Reconstructing Full Unlearned Graphs from Graph Unlearning

arXiv:2511.10936v3 Announce Type: replace-cross Abstract: Graph unlearning (GU) has emerged as a promising solution to comply with 'the right to be forgotten' regulations by enabling the removal of se

GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking

arXiv:2609.39116v1 Announce Type: new Abstract: Prior-free 6D object pose tracking seeks to recover the trajectory of an unseen object from a single RGB video without object-specific CAD models, posed

Agents

Great talk from Yogish Baliga 'From Vim (:wq) to 'You're absolutely right!'' tracing 20+ years of software engineering evolution. Highlights…

Great talk from Yogish Baliga 'From Vim (:wq) to 'You're absolutely right!'' tracing 20+ years of software engineering evolution. Highlights: 1/ open-weight models have closed the gap with closed mode

agentstogether-ai--x

Gromov-Wasserstein Distillation for Inductive Multi-View Embedding

arXiv:2609.40047v1 Announce Type: new Abstract: Gromov-Wasserstein multidimensional scaling (GW-MDS) learns low-dimensional representations from relational data but remains transductive, providing no

applicationsarxiv-cs-lg

GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed

model-releasesarxiv-cs-ai

arXiv:2609.39600v1 Announce Type: cross Abstract: Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal order on output tokens. We vi

Grounding with Confidence: Controllable Generative Video Temporal Grounding

arXiv:2609.39883v1 Announce Type: new Abstract: Video temporal grounding supports applications such as video search, content review, and automated editing by localizing events described in natural lan

Hard-Region Supervision: #1 on the Waymo Open Dataset 2D Video Panoptic Segmentation Leaderboard

arXiv:2609.38714v1 Announce Type: new Abstract: We describe our winning entry to the Waymo Open Dataset 2D Video Panoptic Segmentation Challenge. The task asks for a semantic class at every pixel of e

researcharxiv-cs-cv

HIGS: Hierarchical Implicit Grids for Joint Geometric and Semantic Scene Understanding

arXiv:2609.38620v1 Announce Type: new Abstract: Neural implicit representations have had a significant impact on scene reconstruction by enabling robots to build continuous, differentiable, and high-f

applicationsarxiv-cs-cv

How Should Diffusion Language Models Edit Code?

arXiv:2609.38257v1 Announce Type: cross Abstract: Code editing requires a model to decide where to make changes, generate the new content, and preserve everything else. We study how masked diffusion l

Hybrid Methods for Robust Tabular Data Imputation

arXiv:2609.39613v1 Announce Type: new Abstract: Missing data are a fundamental challenge in statistical analysis and machine learning, as the choice of imputation method substantially impacts downstre

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD

arXiv:2507.12133v2 Announce Type: replace Abstract: Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Finge

hardwarearxiv-cs-lg

Hyperbolic Prototype Routing for Rehearsal-Free Class-Incremental Learning

arXiv:2609.39550v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) aims to continually learn new classes while preserving prior knowledge. Parameter-efficient fine-tuning with pre-traine

Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

arXiv:2512.19735v4 Announce Type: replace Abstract: Accurately predicting mortality risk in intensive care unit (ICU) patients is critical for clinical decision-making. Large language models (LLMs) ar

safetyarxiv-cs-lg

Inductive Visual Logic for Few-Shot Out-Of-Distribution Adaptation in VLMs

model-releasesarxiv-cs-cv

arXiv:2609.38362v1 Announce Type: new Abstract: Generative vision-language models (VLMs) such as Qwen-VL and LLaVA achieve strong zero-shot performance on tasks overlapping with their pretraining dist

Interestingly, just overheard in @swyx podcast interviewing an OpenAI engineer, their Decision API is literally built on GPT-6 Luna adding a…

researchsebastian-raschka--x

During a Swyx podcast interview in October 2026, an OpenAI engineer revealed that the company’s Decision API is built on the GPT‑6 Luna model, augmented with a dedicated decision head. This configurat

Introducing the Server Side Cloud Swift SDK

model-releasesgoogle-cloud-ai

For years, Swift was perceived mainly as a UI language tied to Apple client devices. With the release of Swift 6 and strict concurrency checking, Swift has matured into a premier systems with cloud en

Is Better Teacher Supervision Enough? Unlocking Student-side Learning in Multimodal On-Policy Distillation

arXiv:2609.39120v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning by providing token-level supervision from a teacher on a student's own trajectories. Existing methods pr

safetyarxiv-cs-cv

Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions

arXiv:2609.39608v1 Announce Type: new Abstract: Rule-based reasoning, as in eligibility checks and contract reviews, requires language models to assess evidence against individual conditions and combi

researcharxiv-cs-cl

ITO: Multi-View Alignment and Training-Time Fusion for Image-Text Pretraining

arXiv:2603.02767v4 Announce Type: replace-cross Abstract: Image--text contrastive pretraining has become a dominant paradigm for visual representation learning, yet existing methods often yield repres

JARQ: Joint Alternating Refinement for Quantization

arXiv:2609.38599v1 Announce Type: new Abstract: Group-wise post-training quantizers for large language models round weights onto a grid that is not refit to the resulting integer codes. We show that t

LEAP: Learned Block-wise Evidence Retrieval for Long Audio-Video Perception

arXiv:2609.39938v1 Announce Type: cross Abstract: Hour-scale audio-visual question answering is constrained by a context dilemma: dense whole-recording encoding rapidly exhausts context limits, wherea

local-aiarxiv-cs-ai

LEARN-TS: LLM-Enhanced Alignment and Reconstruction with Normality Guidance for Multivariate Time-Series Anomaly Detection

arXiv:2609.38789v1 Announce Type: new Abstract: Reconstruction errors in multivariate time-series anomaly detection may not reliably distinguish abnormal behavior from benign deviations. Language-deri

safetyarxiv-cs-lg

Learning Normal Diffusion Dynamics for Backdoor Defense in Text-to-Image Models

arXiv:2609.39548v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the secure deployment of text-to-image (T2I) diffusion models. Existing defenses typically detect backdoors

LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems

arXiv:2609.38381v1 Announce Type: cross Abstract: AI-enabled Cyber-Physical Systems (CPS) are highly vulnerable to adversarial and anomalous inputs, where small perturbations can induce cascading erro

applicationsarxiv-cs-ai

Loop-Free Inverse Reinforcement Learning via Sequential Value Recovery with Q-Score Matching

arXiv:2609.38955v1 Announce Type: cross Abstract: Inverse Reinforcement Learning (IRL) aims to recover a reward function that explains expert demonstrations. Existing IRL methods typically rely on a b

Magic-W0: A Structured World-Action Foundation Model for Physical Intelligence

arXiv:2609.39870v1 Announce Type: new Abstract: World-action models (WAMs) augment robot policies with action-conditioned environment dynamics, yet existing approaches largely rely on future observati

researcharxiv-cs-ro

Markovian Dynamics Enforcer: Feasibility Preserving Correction on Learned Dynamics Manifolds

arXiv:2609.39888v1 Announce Type: new Abstract: Neural trajectory predictors can reach low prediction error while violating dynamics, actuator limits, or state constraints, especially when controls ar

Agents

MemCodex: Self-Programming Hierarchical Memory for Language Agents

arXiv:2609.39765v1 Announce Type: new Abstract: Agent memory faces heterogeneous access needs: a single-hop question may require one piece of evidence, whereas a multi-hop question must combine eviden

agentsarxiv-cs-cl

MEMO: Multi-Level Entity-Aware Memory for Streaming Video Understanding

arXiv:2609.38900v1 Announce Type: new Abstract: Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons,

hardwarearxiv-cs-cv

MindWorldBench: Evaluating Mental-State-to-Behavior Reasoning in Image-to-Video Generation

arXiv:2609.39147v1 Announce Type: new Abstract: Current image-to-video models achieve visual realism and physical plausibility, but reasoning about mental states remains unexplored. Actions are driven

safetyarxiv-cs-cv

Tutorials

ModSec-Learn: Boosting ModSecurity with Machine Learning

arXiv:2406.13547v2 Announce Type: replace Abstract: ModSecurity is widely recognized as the standard open-source Web Application Firewall (WAF), maintained by the OWASP Foundation. It detects maliciou

tutorialsarxiv-cs-lg

MotionWeave: Learning Motion-Centered Future Dynamics for Vision-Language-Action Policies

arXiv:2609.39324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently incorporated world models to provide richer dynamic supervision beyond sparse action labels. However

Multi-LLM Collaborative Alignment via Stackelberg Games

arXiv:2609.39076v1 Announce Type: new Abstract: A pool of language models can collaborate and improve collectively by learning from one another's responses. These interactions depend on the instructio

Multimodal Flow: Unified Flow Modeling of Language and Vision in Embedding Spaces

model-releasesarxiv-cs-cv

arXiv:2609.40362v1 Announce Type: new Abstract: We present Multimodal Flow, a fully continuous generative model of language and vision. Most unified multimodal models either model both language and qu

NavHarness: Adaptive Goals for Agentic Vision-Language Navigation

arXiv:2609.39915v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents

NeurDuo-EEG: A Long-Sequence EEG Foundation Model with Persistent State and Explicit Memory

arXiv:2609.38587v1 Announce Type: new Abstract: Electroencephalography (EEG) is recorded continuously over hours, with relevant dynamics spanning timescales from milliseconds to hours. Most EEG founda

NodeGround: A Node Classification Benchmark in the Graph Foundation Model Era

arXiv:2609.39673v1 Announce Type: new Abstract: Can a pretrained graph model replace training and tuning a separate predictor for each dataset? Answering this requires evaluating prediction quality al

OPSRD: On-Policy Self-Role Distillation

arXiv:2609.39884v1 Announce Type: cross Abstract: Role prompting elicits specialized behavior from large language models through an expert identity, offering a lightweight way to guide reasoning on de

PARK: Accurate Block Retrieval for Sparse Attention in Video Diffusion Transformers

arXiv:2609.38978v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a dominant architecture for video generation, but their efficiency is limited by the quadratic complexity of f

hardwarearxiv-cs-cv