Search: “banking”

The Geometry of Inference in Transformer Residual Streams

arXiv:2609.37824v1 Announce Type: new Abstract: Transformer language models build predictions through successive residual updates, but how their representations become specific to an eventual outcome

safetyarxiv-cs-cl

30 Sept 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning

DGX agent

arXiv:2609.37519v1 Announce Type: cross Abstract: Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched d

model-releasesarxiv-cs-ai

30 Sept 2026

World4Scorer: Outcome-Grounded World Modeling for Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2609.36438v1 Announce Type: new Abstract: Autonomous driving requires choosing a safe and efficient plan as surrounding traffic evolves. Generate-and-select planners propose multiple trajectorie

30 Sept 2026

Can Protein-Derived Knowledge Improve Pathology Foundation Models?

arXiv:2609.33178v1 Announce Type: new Abstract: Molecularly guided pathology foundation models (PFMs) exploit transcriptomic or proteomic information to enrich whole-slide image (WSI) representations,

Continual Data Unlearning in Diffusion Models via Transition-based Regularization

arXiv:2609.32328v1 Announce Type: new Abstract: Data unlearning in diffusion models aims to remove the influence of specific training examples without suppressing the broader concepts they represent.

FailPatch: Failure Residual Patching for Vision-Language-Action Models

arXiv:2609.34175v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are typically adapted using successful demonstrations, which provide direct action supervision but rarely cover fa

safetyarxiv-cs-ro

Tutorials

Geometric Inductive Biases for Semi-Supervised Equalization: The Constellation-Aware Transformer

arXiv:2609.33695v1 Announce Type: new Abstract: Decoding signals over unknown channels with minimal pilot overhead is a critical challenge in next-generation communications. Existing deep learning app

tutorialsarxiv-cs-lg

KeyRec: Bounded Visual Memory for Streaming and Long-Video Understanding

arXiv:2609.32182v1 Announce Type: new Abstract: Vision-language models are increasingly used to understand long videos and continuous streams. However, dense visual tokens accumulate with video durati

RefineDrive: Reliable Failure-Guided Learning for Vision-Language-Action Driving

arXiv:2609.35078v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models for autonomous driving rely heavily on successful expert demonstrations, leaving model-specific failures underexploi

safetyarxiv-cs-cv

Semantic Modality Compensation for Unsupervised Visible-Infrared Person Re-identification under Unpaired Settings

arXiv:2609.34294v1 Announce Type: new Abstract: Unsupervised visible-infrared person re-identification (USL-VI-ReID) learns person representations that can be compared across modalities without identi

safetyarxiv-cs-cv

SincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Living

arXiv:2609.34907v1 Announce Type: cross Abstract: Bathroom acoustic-event recognition can support ambient assisted living in settings where continuous video monitoring is undesirable. However, practic

researcharxiv-cs-lg

SubjectAnchor: Subject-Aware Memory-to-Video for Multi-Shot Storytelling

arXiv:2609.34502v1 Announce Type: new Abstract: We present SubjectAnchor, a Subject-Aware Memory-to-Video paradigm for multi-shot storytelling in which the current shot is generated by conditioning on

Synergizing Discriminative Exemplars and Self-Refined Experience for MLLM-based In-Context Learning in Medical Diagnosis

arXiv:2603.27737v2 Announce Type: replace Abstract: General Multimodal Large Language Models (MLLMs) often underperform in capturing domain-specific nuances in medical diagnosis, trailing behind fully

Agents

V-Gym: Enhancing Agentic Visual Reasoning via Skill-Data Co-Evolution

arXiv:2609.34682v1 Announce Type: new Abstract: Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past ex

agentsarxiv-cs-cv

Tutorials

What Should a Streaming Video Model Remember?

arXiv:2606.16353v2 Announce Type: replace Abstract: Streaming video understanding models must answer queries at any moment during an ongoing stream, using only what they have observed so far and under

tutorialsarxiv-cs-cv

When Should a Human Take Back Control? Optimal Delegation under Turbulent AI Risk

arXiv:2609.32083v1 Announce Type: new Abstract: Deploying AI systems requires deciding when to delegate tasks and when humans should intervene to monitor and mitigate risk induced by AI operations. Th

safetyarxiv-cs-lg

Local Ai

Atelier: Learning Local Self-Supervised Features for CryoEM Volumes via Hypernetworks

arXiv:2609.30569v1 Announce Type: new Abstract: CryoEM map interpretation requires features that are spatially localized, consistent across samples, and informative across spatial scales. Most deep le

local-aiarxiv-cs-ai

FeatMark: Feature-level Watermark Protection against Mimicry Attacks with Diffusion Models

arXiv:2609.30980v1 Announce Type: cross Abstract: Text-to-image diffusion models enable data-efficient 'mimicry' attacks, wherein adversaries fine-tune the model on a handful of public photos to synth

PixSim: a calibrated open-source simulator of instant-payment fraud, recovery and interdiction under analyst capacity constraints

arXiv:2609.30684v1 Announce Type: new Abstract: Brazil's Pix settles about 5.9 billion instant, irreversible transfers a month. A fraudulent transfer can be recovered only while the funds remain in a

T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation

arXiv:2609.30576v1 Announce Type: new Abstract: Large-scale recommenders increasingly adopt the sequential generative recipe behind large language models, bringing the Transformer into recommendation

safetyarxiv-cs-ai

AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control

arXiv:2609.30264v1 Announce Type: new Abstract: Latent world models are typically trained to predict factual transitions, whereas model predictive control (MPC) must compare alternative actions from t

researcharxiv-cs-ai

ICE: Task-Aligned Clifford Latent Fields for Multimodal Graph Foundation Models

arXiv:2609.29398v1 Announce Type: new Abstract: Multimodal attributed graphs connect entities, visual content, language, and observed relations. Learning one foundation across such graphs requires mor

researcharxiv-cs-lg

Multimodal Routing and Region Refinement for Language-Guided Medical Image Segmentation

arXiv:2609.28860v1 Announce Type: new Abstract: Textual descriptions can reduce ambiguity in medical image segmentation by specifying the finding and location to be delineated. Existing text-guided me

Training-free Behavior Cloning

arXiv:2609.30134v1 Announce Type: new Abstract: Neural behavior cloning compresses demonstrations into large models, making individual actions difficult to trace and policy updates costly. Retrieval p

safetyarxiv-cs-ro

BranchDrive: A Branch-Structured Dataset for Action-Conditioned Driving Prediction

model-releasesarxiv-cs-ro

arXiv:2609.27275v1 Announce Type: new Abstract: Most autonomous-driving datasets record only the action executed by a behavior policy and the single future that followed, providing limited supervision

MINER: Multi-crop INference-time Enhancement for Rare-Object Retrieval with Frozen Dual Encoders

arXiv:2609.27142v1 Announce Type: new Abstract: Text-to-image retrieval with frozen dual encoders degrades when the query names a small, visually subordinate object in a cluttered scene: a single glob

Predicting Activities in Aqueous Electrolyte Solutions with Hybrid Machine Learning

arXiv:2607.19114v2 Announce Type: replace Abstract: Activities in aqueous electrolyte solutions, usually described by ionic activity and osmotic coefficients, are important properties for modeling man

ScoutNeRV: Rapid Encoding of Grid-Based Video INRs via ScoutNet

arXiv:2609.27958v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a promising paradigm for video compression, providing compact neural representations with flexibl

Agreement Overstates Evidence: Error Dependence in LLM Judge Consensus

arXiv:2609.22512v1 Announce Type: new Abstract: Consensus among LLM judges is often taken as strong evidence that a decision is correct. This assumes that judges make their errors independently. In pr

researcharxiv-cs-ai

Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech

arXiv:2609.24016v1 Announce Type: new Abstract: Commercial large language models are increasingly deployed across African fintech infrastructure for fraud detection and customer communication, yet no

safetyarxiv-cs-ai

COVER: Codec-Robust Video Watermarking with Generative Video Priors

arXiv:2609.26236v1 Announce Type: new Abstract: Video watermarking underpins copyright protection and provenance for generated media, yet almost every video is compressed by a codec before it is store

Destination Support Restoration for Finite-Set Multimodal Trajectory Prediction

arXiv:2609.25942v1 Announce Type: new Abstract: Robots operating around pedestrians often reason over a finite set of predicted human futures. Repeated online updates can concentrate this limited pred

researcharxiv-cs-ro

Differentiable Fuzzy Inference Layer: A Monotone, Compositional Ordinal Reasoning Head for Large Language Models

arXiv:2609.26113v1 Announce Type: new Abstract: A state-of-the-art language model asked to interpret 'most of most students passed' typically answers 'most,' though composing two instances of 'most' y

researcharxiv-cs-cl

gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy

model-releasesarxiv-cs-ai

arXiv:2605.11269v2 Announce Type: replace-cross Abstract: Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast wavef

Latent Dataset Distillation for Human Motion Prediction

arXiv:2609.26430v1 Announce Type: new Abstract: Dataset distillation (DD) compresses a large training set into a compact synthetic set while preserving downstream training utility. Although DD has bee

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

safetyarxiv-cs-cl

SambaGraph: Action-Reaction Spatio-Temporal Graphs for Soccer Tactical Response Modeling

arXiv:2609.25569v1 Announce Type: new Abstract: Soccer tactics are interactive: an attacking action changes the opponent's defensive problem, and the observed response depends on the multi-agent match

Active Visual Sampling with a Connectome-Constrained Fly Model for One-Shot Hatch Recognition in Architectural Drawings

arXiv:2609.24565v1 Announce Type: new Abstract: Architectural drawings encode material classes through repeated hatch patterns. We test whether a connectome-constrained fly visual network, pretrained

CleanScore: Black-Box Benchmark Audits with Negative Controls and Sensitivity Bounds

arXiv:2609.22183v1 Announce Type: new Abstract: Public benchmark scores may reflect skill, prior exposure to the questions, or both, and for most models the training data are unknown. We present Clean

Tutorials

Efficient Reasoning Exploration via State-Conditioned Latent Steering with Progress Guidance

arXiv:2609.24066v1 Announce Type: new Abstract: Best-of-N is a widely used inference strategy for complex reasoning, whose effectiveness depends on whether sampled candidates can cover diverse and hig

tutorialsarxiv-cs-cl

Is Imagination Derived from Hallucination? A Cross-Taxonomy Evaluation of Imagination and Hallucination in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co

MixiMotion: One-Step Text-to-Motion Generation via Asymmetric Set Distillation

arXiv:2609.23010v1 Announce Type: new Abstract: Iterative text-to-motion generation delivers high-quality and semantically aligned motions but requires multiple network evaluations, resulting in subst

safetyarxiv-cs-cv

Preserving Geometric Integrity in Graph Prompting via Measure-Constrained Optimal Transport

arXiv:2609.23547v1 Announce Type: new Abstract: Graph prompt learning enables parameter-efficient adaptation of frozen Graph Neural Networks to downstream tasks through lightweight prompt parameters.

Applications

StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies

arXiv:2609.22684v1 Announce Type: cross Abstract: Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA)

applicationsarxiv-cs-lg

Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking

arXiv:2609.23673v1 Announce Type: new Abstract: In vision-based off-road navigation, a robot needs to know not only which obstacles to avoid but also which terrain is better. The first is handled by f

Agents

AI-GRACE: A Use-Case Operationalization Framework for Agentic AI: From Organizational Objectives and Obligations to Deployment Capabilities and Architecture

arXiv:2609.21192v1 Announce Type: new Abstract: Organizations deploying agentic artificial intelligence must determine more than whether a model is trustworthy; they must establish what to validate, c

agentsarxiv-cs-ai

21 Sept 2026

Chronosphere: Space-Time Tessellation of Local Climate Experts

arXiv:2609.21872v1 Announce Type: new Abstract: We introduce Chronosphere, a spatio-temporal neural field that learns representations of climate. A central challenge in geographic representation learn

21 Sept 2026

Agents

CoLearn: An Agentic Tutor that Learns its Learner in a Human--AI Co-Learning Loop