Search: “banking”

Teacher-Guided Tool Learning for Small Language Models via Bidirectional KL Constraints

arXiv:2610.18459v1 Announce Type: new Abstract: External tools can extend the capabilities of small language models (SLMs), enabling their deployment in resource constrained environments. However, the

safetyarxiv-cs-lg

14 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

DGX agent

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

model-releasesarxiv-cs-ai

12 Oct 2026

Beyond Sequences: Distilling Structured Decision Memory for LLM Recommendation

arXiv:2610.11501v1 Announce Type: new Abstract: Despite the adoption of large language models (LLMs) in recommendation systems, prevailing approaches mostly model single-type behaviors (e.g., views or

researcharxiv-cs-cl

Learning to Retrieve: Internalizing Memory Retrieval for Video World Models

arXiv:2610.11444v1 Announce Type: new Abstract: Video world models aim to generate explorable, 3D-consistent scene videos conditioned on camera trajectories. Existing approaches often rely on external

researcharxiv-cs-cv

NOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM Agents

arXiv:2610.11030v1 Announce Type: cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per ac

One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts

arXiv:2610.12448v1 Announce Type: new Abstract: In this work, we show that a single Transformer block, applied recurrently, can match the accuracy of a full-depth vision encoder at comparable inferenc

ProtoSemImage: Image-Valued Prototypes with Deformable Row Alignment for Interpretable Document Classification

arXiv:2610.11460v1 Announce Type: cross Abstract: Prototypes in classification models are almost always vectors, and a vector has no readable form. This paper asks what happens when a prototype is an

Reliability-Aware Future Conditioning for Temporally Robust Robot Manipulation

arXiv:2610.11956v1 Announce Type: cross Abstract: A generated video of a task the robot is about to perform is useful guidance only if it depicts the phase the robot is actually in. We show that tempo

safetyarxiv-cs-lg

SpikeSSL: A Universal Spike Inference Framework with Dynamics-Informed State-Space Layers

arXiv:2610.11456v1 Announce Type: new Abstract: Two-photon calcium imaging is a standard tool for recording large neural populations in vivo, yet inferring spikes accurately across the growing diversi

World-Model Policy Arbiter for Goal-Conditioned Reinforcement Learning

arXiv:2610.10932v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) has produced a diverse set of goal-reaching algorithms, yet no single algorithm performs best acr

safetyarxiv-cs-lg

Hardware

LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations

arXiv:2610.10465v1 Announce Type: new Abstract: Real-time whole-body controllers for legged robots typically plan through a fixed nominal model and degrade when the deployed dynamics change. Adaptive

hardwarearxiv-cs-ro

8 Oct 2026

PatchBench: Measuring Collateral Damage in Activation Patching

model-releasesarxiv-cs-cl

arXiv:2610.10276v1 Announce Type: cross Abstract: An LLM safety patch can pass a benchmark while still being a poor repair. This risk is especially acute for jailbreak repairs, where the goal is to co

8 Oct 2026

The Identifiability and Observability of Deep Normalized Attention

arXiv:2610.09620v1 Announce Type: new Abstract: We study which parameters of deep, unmasked, single-head attention are determined by its input--output function. For known positive nonconstant real-ana

researcharxiv-cs-lg

8 Oct 2026

ActTune: Action-Aware Precision and GPU Operating-Point Adaptation for Energy-Efficient Vision-Language-Action Inference

model-releasesarxiv-cs-ro

arXiv:2610.08444v1 Announce Type: new Abstract: Vision-language-action (VLA) policies repeatedly invoke inference to control robots, making graphics processing unit (GPU) energy a recurring cost of ta

Agents

AMBER: Training Long-Horizon Web Agents through Append-Only Memory

arXiv:2610.07118v1 Announce Type: new Abstract: Modern language-model agents increasingly interact with external environments over long-horizon, multi-step trajectories, where the accumulated interact

agentsarxiv-cs-ai

DAEDALUS: Bootstrapping Agent Memory from Self-Generated Tasks

arXiv:2610.08048v1 Announce Type: new Abstract: LLM agents often lack the operational knowledge to act reliably in new environments, as they must discover specific tool behaviors or environment conven

Local Ai

From Shared Demand Patterns to Local Uncertainty: Probabilistic Load Forecasting by Mixing Compact Adaptations

arXiv:2610.08538v1 Announce Type: cross Abstract: Probabilistic load forecasting has been widely studied for power-system operation and planning, but customer- and transformer-level forecasting introd

local-aiarxiv-cs-ai

Applications

Low-Rank and Structured Sparse Tensor Decomposition for Anomaly Detection in Multivariate Functional Data

arXiv:2610.06930v1 Announce Type: cross Abstract: Multivariate functional data arise in many modern manufacturing systems, where multiple sensors record densely sampled process trajectories. Monitorin

applicationsarxiv-cs-lg

ServeLearnBench: How Well Can Agents Self-Improve from Serving Experience?

arXiv:2610.07792v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct

A State Based Dispatch Controller for Hospital Delivery Robots with Shared Human and Infrastructure Resources

model-releasesarxiv-cs-ro

arXiv:2610.05971v1 Announce Type: new Abstract: Robot delivery studies can overstate transport capacity when travel to pickups and human support fall outside the modeled schedule. We formulate a locat

Efficient Analog-Initialized Latent Transport for Spatially Coherent Probabilistic Downscaling from Global to Kilometer Scales

arXiv:2610.03736v1 Announce Type: cross Abstract: Probabilistic downscaling must represent kilometer-scale structure left unresolved by a deterministic regional prediction. We introduce an analog-init

Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts

arXiv:2610.06147v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time. Test-time adapta

M^2-Occ: Resilient 3D Semantic Occupancy Prediction for Autonomous Driving with Incomplete Camera Inputs

arXiv:2603.09737v2 Announce Type: replace Abstract: Semantic occupancy prediction enables dense 3D geometric and semantic understanding for autonomous driving. However, existing camera-based approache

NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI

arXiv:2610.06502v1 Announce Type: new Abstract: Content-based image retrieval (CBIR) in neuroimaging enables the identification of structurally similar brain scans, supporting diagnosis, prognosis, an

researcharxiv-cs-cv

REFLEX: Reflective Evolution from LLM Experience

arXiv:2606.16496v2 Announce Type: replace-cross Abstract: Large multimodal language models (MLLMs) have emerged as powerful tools for guiding evolutionary search toward interpretable programmatic poli

researcharxiv-cs-lg

What Gradients Add to Text Leakage in Split Language Models, Counted per Token and per Document

arXiv:2610.04128v1 Announce Type: cross Abstract: Split learning lets a client train a language model on a server without sending its text. The client runs the first layers itself and sends the server

Does Every User Need a Private LoRA? Decoupling Personalization from Per-User Adaptation

arXiv:2610.02353v1 Announce Type: cross Abstract: Personalized large language models often require a complete adaptation state for each user. However, this paradigm scales poorly as the user populatio

researcharxiv-cs-cl

Evaluation format, not model capability, drives measured triage failure in the assessment of consumer health AI

arXiv:2603.11413v4 Announce Type: replace-cross Abstract: A recent Nature Medicine study reported that ChatGPT Health under-triages 51.6% of emergencies and concluded that consumer-facing AI triage po

Agents

From Benchmarks to Production: A Text-to-SQL System for Complex Financial Data

arXiv:2610.03524v1 Announce Type: new Abstract: General-purpose Text-to-SQL systems achieve strong performance on academic benchmarks like Spider and BIRD, where schemas are relatively shallow and col

agentsarxiv-cs-ai

Verifiable, Articulable, and Tacit Components of Preference

arXiv:2610.03025v1 Announce Type: new Abstract: What makes a short story gripping; a news article newsworthy; or a math proof elegant? These constructs resist articulation or verification; their meani

FFBL-Coop: Association-Decoupled Cooperative 3D Multi-Object Tracking

arXiv:2610.01750v1 Announce Type: new Abstract: Cooperative 3D tracking must integrate complementary observations across agents and time while maintaining consistent identities. When evidence integrat

Madeleine: Learning Involuntary Recall for Conversational Memory from Simulated Lives

arXiv:2610.01118v1 Announce Type: cross Abstract: A long-term conversational assistant must recall the right memory at the right moment, yet the memory that matters most is often not similar to what t

Platonic Task Arithmetic

arXiv:2610.00929v1 Announce Type: cross Abstract: Models specialized for the same task converge to similar behavior, yet the parameter updates that produce it share no common coordinate system, so wei

The Hidden Costs of 99% Accuracy: A Trustworthiness Audit of the Telco Customer Churn Benchmark

arXiv:2610.00118v1 Announce Type: new Abstract: Customer churn prediction on the IBM Telco Customer Churn benchmark (n = 7,043) routinely reports test accuracies above 95%, with the most cited publish

CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series

arXiv:2609.39484v1 Announce Type: cross Abstract: Longitudinal clinical cohorts are multimodal, irregularly sampled and pervasively incomplete: in ADNI, positron emission tomography and cerebrospinal

researcharxiv-cs-ai

Applications

DCM-SAM: Defect-Conditioned Mixture of LoRA Experts for NPU-Deployed AM Defect Segmentation

arXiv:2609.38811v1 Announce Type: new Abstract: Metal additive manufacturing parts are inspected by X-ray computed tomography, where labelled data is scarce, the pores and inclusions that matter span

applicationsarxiv-cs-cv

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning,

Graph Anomaly Detection as Finite-Horizon Control: Training-Free Scoring via Empirical Bayes

arXiv:2609.38424v1 Announce Type: new Abstract: Node-level graph anomaly detection (GAD) identifies nodes whose attributes and interactions deviate from dominant graph regularities. Existing GAD model

researcharxiv-cs-lg

Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model

arXiv:2609.39794v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, yet adapting them to new tasks and domains remai

LOCI: Spatial Linear Memory for Streaming World Models

arXiv:2609.40222v1 Announce Type: new Abstract: When a camera revisits a previously observed region, a video world model should reproduce what was there before. This requires both remembering past obs

Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models

model-releasesarxiv-cs-cl

arXiv:2609.39346v1 Announce Type: new Abstract: Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (SL

Ready2Blend: From Natural-Language Instructions to Composable Alignment Prompts

arXiv:2609.39365v1 Announce Type: cross Abstract: Continual alignment requires LLMs to adapt to new requirements without forgetting previously acquired behaviors. Natural-language instructions are fle

Restoring without Forgetting: Filter-Level Continual Image Restoration via Parameter-Space Integrated Gradients

arXiv:2609.38591v1 Announce Type: new Abstract: Adapting image restoration models to a stream of new tasks without revisiting past data remains challenging due to catastrophic forgetting. In this work

T-Router: Learning Thalamic Routing for Reasoning with Parameter-Efficient Reinforcement Learning

arXiv:2609.39109v1 Announce Type: cross Abstract: Parameter-efficient reinforcement learning aims to improve reasoning with a compact trainable interface to a pretrained model. We introduce the Thalam

Byzantine-Robust Federated Representation Learning

arXiv:2609.36660v1 Announce Type: new Abstract: We study federated learning (FL) with adversarial clients, where the goal is to minimize the average loss of the honest (non-adversarial) clients withou

FLASH: A 'Generate Once, Synthesize Many' Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection

arXiv:2609.37314v1 Announce Type: new Abstract: Synthetic anomaly generation helps expand industrial anomaly datasets when real defects are scarce or unavailable. Existing approaches lie at two extrem

researcharxiv-cs-cv

LatentSift: Policy-State Filtering for Token-Efficient Verification of Software Engineering Agents

arXiv:2609.36371v1 Announce Type: cross Abstract: Test-time scaling improves software engineering agents by generating multiple candidate trajectories and selecting the best one. Verifying and selecti

safetyarxiv-cs-ai

Self-Aligned Forcing: Streaming Video Diffusion with Differentiable Noisy History

arXiv:2609.38114v1 Announce Type: new Abstract: Autoregressive video diffusion enables interactive streaming generation, but suffers from error accumulation over long rollouts. Self-rollout training r

safetyarxiv-cs-cv