Search: “framework”

Temporal Evidence Forests for Long-Horizon Multi-Party Conversational Memory

model-releasesarxiv-cs-cl

arXiv:2610.12874v1 Announce Type: new Abstract: Long-term memory has been widely adopted in LLM-based agents to support persistent interaction and personalized assistance. Long-term multi-party intera

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels

DGX agent

arXiv:2610.13221v1 Announce Type: new Abstract: Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets

researcharxiv-cs-lg

12 Oct 2026

Time Delay System for Sequence Modeling

arXiv:2610.12864v1 Announce Type: new Abstract: Existing sequence models share a critical limitation: they lack an explicit, interpretable mechanism for content-aware temporal recall. LSTMs compress e

researcharxiv-cs-cl

VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning

model-releasesarxiv-cs-ai

arXiv:2610.13098v1 Announce Type: new Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous su

Vision for engineering, manufacturing, and earth observation. Checks mechanical parts, pulls evidence from PDFs, scans gigapixel satellite i…

applicationsmistral-ai--x

Mistral AI outlines its vision for engineering, manufacturing, and earth observation by demonstrating how the model can inspect mechanical components, extract evidence from PDFs, and analyze gigapixel

X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems

arXiv:2610.13886v1 Announce Type: new Abstract: Personal agents increasingly connect to services across the web and applications by using tools. As the effects of their actions accumulate and interact

agentsarxiv-cs-ai

AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems

arXiv:2509.02302v2 Announce Type: replace Abstract: We study history-dependent online problems with a possibly inaccurate prediction of the future request sequence. Motivated by several real-world app

applicationsarxiv-cs-lg

AgentFly: Scaling Agentic Reinforcement Learning with Unified Resource System

arXiv:2507.14897v2 Announce Type: replace Abstract: Methods to build LLM agents have evolved from prompt engineering and supervised finetuning to agentic reinforcement learning (agentic RL). However,

agentsarxiv-cs-ai

Ambient Discrete Diffusion: Using the Wrong Data at the Right Time for Data Efficient Learning

arXiv:2610.12340v1 Announce Type: new Abstract: We introduce RefineMix, a framework for training discrete diffusion models under severe data scarcity, a common constraint in scientific applications. R

tutorialsarxiv-cs-lg

An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networks

arXiv:2610.11537v1 Announce Type: cross Abstract: Flow models generate trajectories from an initial distribution to a target distribution by solving an ordinary differential equation defined by a velo

Barron Optimal Transport I: Generative Modeling

arXiv:2610.10875v1 Announce Type: new Abstract: Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the not

Best of Both Worlds in Federated LSA: Speedup When Possible, Personalization Always

arXiv:2610.11555v1 Announce Type: new Abstract: We study personalized federated linear stochastic approximation (LSA), a framework which notably encompass personalized temporal difference learning. In

agentsarxiv-cs-lg

Bilevel optimization for data-driven learning of Koopman embeddings using kernel-based autoencoders

arXiv:2610.12370v1 Announce Type: new Abstract: Koopman operator theory provides a linear framework for analyzing nonlinear dynamical systems and has become a major tool for data-driven modeling. A ce

tutorialsarxiv-cs-lg

Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy

arXiv:2610.11222v1 Announce Type: cross Abstract: Preclinical models poorly predict human drug efficacy, particularly in neurological disorders. Neural activity offers a uniquely rich source of transl

DAMP: Humanoid Locomotion via Denoised Belief Learning and Adversarial Motion Priors

arXiv:2610.11505v1 Announce Type: new Abstract: Humanoid robots possess the structural capability to traverse complex terrains. However, achieving stable t raversal without relying on perceived inform

safetyarxiv-cs-ro

Equal Path Cost, Unequal Output Effects: Understanding Perturbation Propagation in Diffusion Models

arXiv:2610.11380v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in generative modeling, with their sampling procedures routinely modified to control generation and im

researcharxiv-cs-ai

Fluid-Gen-Zero: Grounding Pretrained Video Generators in Physics without Training

arXiv:2610.10984v1 Announce Type: new Abstract: We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from

Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

arXiv:2510.04440v2 Announce Type: replace Abstract: We develop a source-driven fractional heat-kernel framework for semi-super-vised graph learning that combines nonlocal propagation with sustained la

Fresco++: Frequency-Guided and Canonical-Consistent Optimization for Fine-Grained Head Avatar Modeling

arXiv:2610.11412v1 Announce Type: new Abstract: We propose Fresco++, a unified optimization framework for fine-grained and view-consistent head avatar reconstruction. Head avatar optimization is typic

researcharxiv-cs-cv

From Language to Motion: Task-Conditioned Focal-Stack Trajectory Integration for Microscopic Robots

arXiv:2610.12241v1 Announce Type: new Abstract: Microscopic robots require accurate task geometry despite changes in language, parts, and focus. We present a semantic-to-physical framework that maps i

researcharxiv-cs-ro

OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3D Cinemagraphs

arXiv:2610.12461v1 Announce Type: new Abstract: Recent 3D world models generate photorealistic, explorable scenes that remain frozen in time. OuroWorld is a mask-free framework that turns any static 3

tutorialsarxiv-cs-cv

Ranking Prior Alignment for Credit Risk Modeling: When Do External Priors Matter?

arXiv:2610.11146v1 Announce Type: new Abstract: Cold-start credit scoring -- deploying models with scarce labeled data, weak features, or minimal capacity -- is a recurring problem in financial machin

Rewiring Semantics, Dynamics, and Control: A Simple yet Effective Action-Centric Tri-Stream Transformer

arXiv:2610.11416v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent framework for complex robotic manipulation, building on the strong semantic understand

applicationsarxiv-cs-ai

Strategic Investment Decision Making for Value Creation in Energy Transition: A Reinforcement Learning Approach

arXiv:2610.10768v1 Announce Type: cross Abstract: The global challenge of climate change has driven significant steps to reduce CO2 emissions, guided by international agreements like the Paris Agreeme

Symbolic Density Estimators for Unnormalized Distributions

arXiv:2610.10807v1 Announce Type: new Abstract: Estimating the symbolic or analytical form of probability density functions (PDFs) from observed samples is a fundamental challenge in statistical and c

The optimal information complexity of VC learning

arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori

Towards Path-Creative Navigation: Robot Navigation through Embodied Interaction

arXiv:2610.11072v1 Announce Type: new Abstract: Autonomous navigation in cluttered and constrained environments typically assumes a fixed environment and searches only for paths within existing free s

agentsarxiv-cs-ro

Uncovering and Fixing Collider Bias in Bayesian PINNs

model-releasesarxiv-cs-ai

arXiv:2610.11737v1 Announce Type: cross Abstract: Bayesian physics-informed neural networks (B-PINNs) are a popular framework for parameter and state inference from sparse or noisy observations. They

A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding

arXiv:2610.08792v1 Announce Type: new Abstract: We present a foundational formulation of the Bayesian Mirror Architecture (BMA), a self-referential generative framework in which sensory abstractions,

tutorialsarxiv-cs-lg

A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation

arXiv:2610.10116v1 Announce Type: new Abstract: Semantic segmentation networks operate on a fixed set of classes and therefore fail when out-of-distribution (OOD) objects appear during deployment, a c

Adaptive Code Generation for Controlling Robots

arXiv:2610.09588v1 Announce Type: new Abstract: Deploying robots as Complex Adaptive Systems (CAS) in unknown and dynamic environments necessitates a transition from rigid command libraries toward int

researcharxiv-cs-ro

Adjoint-Based Calibration and Optimal Control of Stochastic Multiscale Bioprocess Digital Twins

arXiv:2610.09505v1 Announce Type: cross Abstract: We develop a bias-aware digital-twin calibration and control framework for multiscale bioprocess models within a biological systems-of-systems (Bio-So

Beyond Anonymous Captions: Grounding Character Identity in Video Captioning and Question Answering

arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-awa

Beyond Explanation: Debugging Medical Imaging Models via Concept Intervention

arXiv:2610.09031v1 Announce Type: new Abstract: Medical imaging models often operate as black boxes, limiting interpretability and systematic debugging. We introduce an easy-to-use, plug-and-play fram

researcharxiv-cs-cv

Beyond Risk Prediction: Evidence Grounding and Psychosocial Factor Verification for Explainable Suicide Risk Assessment

arXiv:2610.08842v1 Announce Type: new Abstract: Identifying suicide risk from social networking services (SNS) posts is important for detecting suicide-related signals in online environments. However,

researcharxiv-cs-cl

Bi-CamoDiffusion: A Boundary-informed Diffusion Approach for Camouflaged Object Detection

arXiv:2603.13357v2 Announce Type: replace Abstract: Bi-CamoDiffusion is introduced, an evolution of the CamoDiffusion framework for camouflaged object detection. It integrates edge priors into early-s

Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation

arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drif

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

safetyarxiv-cs-cl

Decoupled Optimization for Teacher-Student Semi-Supervised Learning via a Pioneer Student

arXiv:2610.09609v1 Announce Type: new Abstract: Semi-supervised learning (SSL) relies on two core mechanisms: self-training under the Teacher-Student (T-S) framework and joint optimization of labeled

ExperienceIndex: Artifact-Grounded Memory

arXiv:2610.10091v1 Announce Type: new Abstract: Knowledge-intensive tasks require answering many questions by reasoning about a shared corpus of artifacts (e.g., court cases, or scientific literature)

agentsarxiv-cs-cl

Finding the Right Balance: Relevance and Diversity in LLM Retrieval

arXiv:2610.09412v1 Announce Type: cross Abstract: Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves re

applicationsarxiv-cs-cl

GPU - Vulkan llama.cpp benchmarks sorted by price to performance

model-releasesr-localllama

This table to help anyone looking to build a budget Data Center homelab. I copied the bulk of value based, mid level, decent speed results GPUs and feed it to AI or SI and here are the recommended res

HuMBLE: Human Motion-Driven Behavior Learning for Embodied Locomotion

arXiv:2610.10489v1 Announce Type: new Abstract: Despite recent advances in humanoid locomotion, controllers optimized for command tracking and robustness tend to produce mechanical gaits, whereas cont

safetyarxiv-cs-ro

Kinetic Langevin Meets Split Gibbs: Accelerated Posterior Sampling for Imaging Inverse Problems with Diffusion Priors

arXiv:2610.10187v1 Announce Type: cross Abstract: Split Gibbs sampling (SGS) is a popular framework for posterior sampling in Bayesian imaging inverse problems. It decouples a Gaussian data-fidelity t

Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

arXiv:2610.10351v1 Announce Type: cross Abstract: Differentiable quantum architecture search (DQAS) is a promising framework for the automated design of quantum circuits, particularly for variational

MUNITE: Unified Multimodal Latent Inference for Any-to-Any Multimodal Generation

arXiv:2610.09866v1 Announce Type: new Abstract: We introduce MUNITE, a latent-variable framework for flexible any-to-any multimodal generation that treats encoding and latent generation as the same in

safetyarxiv-cs-lg

One-Shot Adaptive Segmentation For Scientific Images

arXiv:2610.10306v1 Announce Type: new Abstract: Scientific image segmentation methods rely on extensive annotation and task-specific training, limiting adaptation across imaging modalities and experim

researcharxiv-cs-cv

PhysEvo: Astra Can Act, Let It

arXiv:2610.08995v1 Announce Type: new Abstract: Astra can act, yet reliable manipulation depends on the system through which it observes and controls the world. We introduce PhysEvo, a framework for p

safetyarxiv-cs-ro