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Formalizing Forgetting: Theory of Forgetting for Online Continual Learning

arXiv:2610.14787v1 Announce Type: new Abstract: Online continual learning (OCL) requires a learner to acquire a sequence of tasks in a single pass over the data, and catastrophic forgetting of earlier

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Foundation Models for Event Prediction Across Heterogeneous Event Logs

DGX agent

arXiv:2610.17503v1 Announce Type: new Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational syste

model-releasesarxiv-cs-lg

14 Oct 2026

Hardware

FoundationVIO: Enforcing Metric Scale in Feed-forward Visual-Inertial Odometry

arXiv:2610.14951v1 Announce Type: new Abstract: Feed-forward geometric foundation models (GFMs) directly predict dense geometry and camera poses from batches of images. Emerging visual SLAM methods ch

hardwarearxiv-cs-ro

FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models

arXiv:2610.16744v1 Announce Type: new Abstract: Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce thi

Agents

FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation

arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu

agentsarxiv-cs-lg

FragFlex: Fragment-Based Flexible Molecular Generation for Exploring Vast Chemical Space

arXiv:2610.15284v1 Announce Type: new Abstract: Drug discovery requires efficient exploration of an astronomically large chemical space. Molecular graph diffusion models offer a promising approach to

Tutorials

FrameFold: Response-Guided KV Cache Consolidation for Autoregressive Long Video Generation

arXiv:2610.14568v1 Announce Type: new Abstract: In autoregressive video generation, retaining all historical key-value (KV) states increases memory usage and per-step attention costs as videos grow lo

tutorialsarxiv-cs-cv

Local Ai

FrameLite: Decision-Oriented Aesthetic Cropping with a Compact Vision-Language Model

arXiv:2610.17639v1 Announce Type: new Abstract: Aesthetic image cropping improves composition by balancing subjects, context, and image boundaries. Large vision-language models bring semantic knowledg

local-aiarxiv-cs-cv

FreeCHROMA: Generative Chroma Keying from Unaligned Background References

arXiv:2610.14445v1 Announce Type: new Abstract: In film production, chroma keying composites an approved foreground performance into a new environment, but conventional workflows require coordinated b

FreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation

arXiv:2610.17191v1 Announce Type: new Abstract: Linear-time sequence models typically store long-context information in a recurrent state. A fixed-size state limits how much information can be stored,

Frequency Routing and Identity Conditioning for Thermal-to-Visible Face Translation

arXiv:2610.17859v1 Announce Type: new Abstract: Thermal-to-visible (T2V) face translation has important applications in nighttime biometric recognition, low-light surveillance, and human interpretatio

Frequency-Step Cache: Separating Synchronization and Repair for Efficient Autoregressive Video Diffusion

arXiv:2610.15922v1 Announce Type: new Abstract: Autoregressive (AR) video generation enables long-horizon synthesis but requires repeated forward passes through large diffusion transformers. Training-

Applications

From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction

arXiv:2610.16569v1 Announce Type: cross Abstract: Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance lab

applicationsarxiv-cs-lg

Agents

From Acoustic Sensing to Physical Actions: A Comprehensive Survey of Security Risks in Edge-Deployed Audio LLM-Based Agents

arXiv:2610.15390v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) are embedded in agents for smart homes, vehicles, wearables, and embodied systems, where acoustic inputs can

agentsarxiv-cs-cv

From Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs

arXiv:2602.00628v3 Announce Type: replace Abstract: We investigate the extent to which an LLM's hidden-state geometry can be recovered from its behavior in psycholinguistic experiments. Across eight i

From bits to atoms: A survey of cross-layer safety in Embodied AI

arXiv:2610.14038v1 Announce Type: new Abstract: Embodied Artificial Intelligence (AI) introduces cyber-physical risks because digital failures and attacks can cause physical harm. This survey organize

From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathology

arXiv:2511.11984v2 Announce Type: replace Abstract: Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-l

From Failure Prediction to Component Selection in Semantic Segmentation

arXiv:2610.16058v1 Announce Type: new Abstract: Reliable scene understanding requires deciding which predictions to trust, retain, or inspect. In semantic segmentation, component failure predictors su

From Field to Planning: Learning Temporal Polar Gradient Fields for Vision-based AAV Trajectory Planning in Dynamic Environments

arXiv:2610.14482v1 Announce Type: new Abstract: Autonomous Aerial Vehicle (AAV) trajectory planning requires real-time and accurate safety gradient guidance, especially in dynamic environments. Existi

From Hitter to Player: Separating Motor Execution and Strategy in Competitive Humanoid Table Tennis

arXiv:2610.14067v1 Announce Type: new Abstract: Competitive humanoid table tennis requires two distinct abilities: executing a desired return and deciding where to return the ball. We separate these t

From hyperplanes to hyperellipsoids: a pedagogical bridge from linear classifiers to single-qubit mixed-state classifiers

arXiv:2607.15433v2 Announce Type: replace Abstract: Quantum machine learning ideas are typically absent from traditional machine learning curricula and are instead introduced in upper-level courses on

From LLM Plans to Authorized Motion: Execution-Bound Authorization for Excavators

arXiv:2610.14245v1 Announce Type: new Abstract: An LLM-directed excavator can execute mechanically feasible motion whose destination or authority no longer matches the operator's approval. We propose

researcharxiv-cs-ro

From Orbit Matching to Docking: A Hierarchical Reinforcement-Learning Approach to Multiphase Rendezvous Trajectory Design

arXiv:2610.17468v1 Announce Type: cross Abstract: As the complexity of space missions increases, autonomous spacecraft guidance must accommodate transitions between mission phases with distinct dynami

safetyarxiv-cs-lg

From Parallel to Sequential: Small-Batch Noise Restores Simplicity Bias of Muon

arXiv:2610.16868v1 Announce Type: new Abstract: Simplicity bias, which can arise from sequential feature learning during training, has been proposed as a general explanation for the success of deep le

safetyarxiv-cs-lg

From Perception to Symbolic Task Planning: Vision-Language Guided Human-Robot Collaborative Structured Assembly

arXiv:2601.00978v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) in structured assembly requires reliable state estimation and adaptive task planning under noisy perception and huma

researcharxiv-cs-ro

Tutorials

From Pixels to Executable Physics: Behavior-Grounded World Models for Embodied Action Consequence Prediction

arXiv:2610.17630v1 Announce Type: cross Abstract: In outdoor environments, varying terrain and contact conditions can cause identical action commands to produce different motion outcomes for quadruped

tutorialsarxiv-cs-cv

From Policy Evaluation to Off-Policy Control: Provable Emergence of In-Context Q-Learning

arXiv:2610.18057v1 Announce Type: new Abstract: Transformers can implement reinforcement-learning algorithms in context, yet how off-policy control emerges within Transformers remains poorly understoo

Local Ai

From Prototype to Massing: Learning Graph Correspondence for Scalable Facade Modeling

arXiv:2610.14098v1 Announce Type: new Abstract: Facade articulation at building scale is usually resolved manually or through parametric systems that encode design intent as explicit rules. This paper

local-aiarxiv-cs-lg

From Rainfall to Road-Network Functionality: Transferable Graph Forecasting for Flood-Disrupted Transportation Networks

arXiv:2610.14622v1 Announce Type: new Abstract: Extreme rainfall can rapidly degrade road-network functionality (RNF), disrupting emergency mobility, accessibility, evacuation, logistics, and infrastr

From Simulated Fluids to Living Tissue: Zero-Shot Foundation Model Transfer to Perturbed Embryos

arXiv:2610.16236v1 Announce Type: new Abstract: Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations

From Sound to Sense: An Anatomy of Semantic Supervision for Speech-Driven Visual Grounding in Remote Sensing Imagery

arXiv:2610.16364v1 Announce Type: new Abstract: Speech-driven visual grounding in remote sensing (RSVG) removes the typing bottleneck of text-based interaction and is intended to preserve prosodic int

safetyarxiv-cs-cv

From Spectral Saliency to Finite Deletion: Evaluating Selective Language Model Edits

arXiv:2610.18098v1 Announce Type: new Abstract: Deleting singular components offers a precise way to remove a capability from a language model, yet the first-order spectral saliency used to rank compo

From Suboptimal to Optimal: One-Step Latent Flow Policies for Offline Reinforcement Learning

arXiv:2610.16984v1 Announce Type: new Abstract: Offline reinforcement learning aims to learn effective policies from fixed datasets without environment interaction. Although generative models such as

From Token Correction to Claim Admission: Training-Free Hallucination Mitigation for Large Vision-Language Models

arXiv:2610.17706v1 Announce Type: new Abstract: Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image. To mitigate this issue, we

From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures

arXiv:2511.22150v3 Announce Type: replace Abstract: Studying the shape of text embedding spaces enhances our understanding of model behavior and how geometry affects downstream task performance. While

From Transfer Probes to Expert Grouping: Evidence from LoRA Post-Training

arXiv:2610.14437v1 Announce Type: new Abstract: A platform that post-trains one base model for many business lines often has more lines than experts it can maintain, so lines must share experts, yet l

From Video to Vision: Learning Generalizable Humanoid Carrying from Human Motion

arXiv:2610.14561v1 Announce Type: new Abstract: Most existing approaches rely on video or motion-capture data for reinforcement learning (RL) training; however, all of these methods require an upper-l

From Volpiano to Pixels: 30,000 Lines of OMR Ground Truth for Medieval Chant

arXiv:2610.16862v1 Announce Type: new Abstract: Optical music recognition (OMR) for medieval chant lacks training data linking manuscript images to musical symbols across notational families. Using ex

safetyarxiv-cs-cv

Frozen History: When Temporal Losses Stop Accumulation in Learned Real-Time Supersampling

arXiv:2610.15752v1 Announce Type: new Abstract: Learned real-time supersampling accumulates jittered low-resolution samples along motion vectors. Many methods use a temporal consistency loss to reduce

Frozen Site-Probe Accuracy Is Not a Standalone Harmonization Score: An Audit of Evaluation Practice for Multi-Site MRI

arXiv:2610.14140v1 Announce Type: cross Abstract: Image-level MRI harmonization is often evaluated with a frozen site probe, a site classifier trained on raw scans and applied unchanged to harmonized

safetyarxiv-cs-cv

Full Waveform Inversion with a Learned Preconditioner

arXiv:2610.15331v1 Announce Type: new Abstract: Full-waveform inversion (FWI) is a powerful approach for reconstructing subsurface velocity models, but its practical performance is limited by ill-cond

FunDM: Cheap & Label-Free Decision Models from Frozen Language Models

arXiv:2610.17175v1 Announce Type: new Abstract: Decision models such as Jev score candidate answers or actions. A small decision head trained label-free can recover about 99% of a frozen language mode

Funnel planning and control for manipulators using neural Signed Configuration Distance Functions

arXiv:2610.14917v1 Announce Type: new Abstract: Robust motion planning and control for manipulators is the problem of guaranteeing safe execution and collision-free motion under disturbances. The Kino

researcharxiv-cs-ro

Local Ai

G^2WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey

local-aiarxiv-cs-ro

GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression

arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts

GAD: Geometry Attention Distillation for Consistent Video Generation

arXiv:2610.18779v1 Announce Type: new Abstract: Video diffusion models generate visually compelling short-term sequences but often struggle to preserve scene geometry and object structure over time. I

Game-Theoretic Reinforcement Learning based Topology-Agnostic Defense for Virtual Power Plants

arXiv:2610.15183v1 Announce Type: new Abstract: The rapid proliferation of distributed energy resources (DERs) aggregated by virtual power plants (VPPs) elevates cybersecurity risk by expanding the at

safetyarxiv-cs-lg

Game2Real-Bench: Do Toy Games Reveal and Transfer to Real-World Visual Reasoning?

arXiv:2610.18834v1 Announce Type: new Abstract: Visual reasoning is an important capability for vision-language models (VLMs) to understand visual evidence, spatial structure, constraints, and state c