Search: “models”

Advancing Wildlife Conservation through Multimodal Animal Re-Identification with Environmental Metadata

arXiv:2609.34094v1 Announce Type: new Abstract: Identifying individual animals is crucial for effective wildlife monitoring and conservation efforts. Recent advancements in computer vision have shown

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Agentic Multi-Turn Reasoning: A Fairness Approach

DGX agent

arXiv:2609.33323v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, v

safetyarxiv-cs-lg

29 Sept 2026

AI-driven ionic liquid discovery with unified chemical intelligence

arXiv:2511.11257v2 Announce Type: replace-cross Abstract: The rational discovery of functional solvents remains challenging because macroscopic solvent behaviors emerge from complex many-body interact

All On-Board: Fully On-Chip Neuromorphic Q-Learning with Embedded CartPole Simulation

arXiv:2609.32317v1 Announce Type: cross Abstract: As AI models grow in size and usage, their energy demands increase dramatically, raising sustainability and economic concerns. Neuromorphic hardware,

Local Ai

Analytical and Convolutional Neural Network-Based Motion-Vector Propagation for Efficient Video Object Detection

arXiv:2609.34142v1 Announce Type: new Abstract: Continuous video analytics requires accurate localization at low latency within embedded power budgets. This paper presents a hardware-software design m

local-aiarxiv-cs-cv

Industry

Anthropic warns of ‘catastrophic’ AI risks in its own IPO filing

As Anthropic gears up for its greatly anticipated public debut, a preview of the company's IPO filing reportedly details its mounting losses, leadership proposals to retain power, and how its AI devel

industrythe-verge-ai

Are agent harnesses dying? What harness distillation changes

Harness distillation can train general scaffolding into a model. The harness that remains is the part tied to your tools, data, users, and environment. The post Are agent harnesses dying? What harness

agentsarize-ai

Assisting for Open-Ended Tasks: Goal-Oriented Shared Autonomy as a Particle Filter

arXiv:2609.32576v1 Announce Type: new Abstract: A common approach for shared autonomy blends human inputs with autonomous assistance based on the human's likely goal. However, most existing approaches

agentsarxiv-cs-ro

Awaken, Then Scale: Tiny Adaptation for MRI Reconstruction

arXiv:2609.31813v1 Announce Type: cross Abstract: Dormant Awakening (DA) specializes a magnetic resonance imaging (MRI) reconstruction model by fitting a small set of zero weights to one labeled slice

Back-Tracking from Clarity: Self-Learning to See Text from Afar

arXiv:2609.32477v1 Announce Type: new Abstract: We propose a self-supervised framework designed to enhance the capability of scene text detectors in identifying and recognizing text in scenarios where

Be Careful Who You Trust: Coordination Dynamics under Corrupted Communication in LLM Multi-Agent Games

arXiv:2609.31704v1 Announce Type: cross Abstract: Large language models are increasingly used as interacting agents, but it remains unclear how robust their coordination is when public communication i

Beyond Energy: When Sustainability Dimensions Reshape LLM Serving Decisions

arXiv:2609.35569v1 Announce Type: cross Abstract: Large language model (LLM) serving has environmental impacts across energy consumption, carbon emission, water consumption, and biodiversity loss. Yet

Beyond Token Scale: Chunk-Level Sparse Autoencoders for Reliable Semantic Feature Discovery

arXiv:2609.35521v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) expose features that help us understand and steer language models, but faithful reconstruction does not guarantee informati

Local Ai

Binaural Audio-Visual Instance Segmentation

arXiv:2609.32180v1 Announce Type: new Abstract: Audio-visual segmentation (AVS) aims to segment sounding objects at the pixel level by integrating auditory and visual cues. However, existing methods a

local-aiarxiv-cs-cv

BudgetVerify: Budget-Tiered Verification for Financial QA

arXiv:2609.33052v1 Announce Type: cross Abstract: Financial question answering often requires precise numerical extraction, unit handling, and arithmetic over tables and text, but applying expensive v

Can Circuit Alignment Predict OOD Generalization?

arXiv:2609.31996v1 Announce Type: new Abstract: Can out-of-distribution (OOD) generalization be predicted from a trained model's weights alone, without any target-domain data? Existing representationa

Tutorials

CAT: Can Trust be Predicted with Context-Awareness in Dynamic Heterogeneous Networks?

arXiv:2512.11352v2 Announce Type: replace Abstract: Trust prediction provides valuable support for decision-making, risk mitigation, and system security enhancement. Recently, Graph Neural Networks (G

tutorialsarxiv-cs-lg

Certified Multi-Source Integrity for Structured Agent Actions

arXiv:2609.34245v1 Announce Type: cross Abstract: LLM agents increasingly take privileged, often irreversible structured actions, such as paying an invoice. They assemble each action from action-criti

CityToolVQA: Tool-Augmented Visual Question Answering for 3D Spatial Cognition in Urban Low-Altitude Environments

arXiv:2609.32427v1 Announce Type: new Abstract: CityToolVQA addresses the weak performance of Vision-Language Models (VLMs) on quantitative tasks in urban low-altitude visual question answering. We di

Constrained Edit Fields for Training-Free Flow Editing

arXiv:2609.33735v1 Announce Type: new Abstract: Text-guided image editing aims to perform a desired edit while preserving source content unrelated to it. Pretrained rectified-flow models enable traini

safetyarxiv-cs-cv

Applications

Coverage-aware Semantic Representation Learning for Underrepresented Visual Concepts

arXiv:2602.16917v2 Announce Type: replace Abstract: Modern vision models increasingly rely on rich semantic representations that extend beyond class labels to include descriptive concepts, attributes,

applicationsarxiv-cs-cv

Applications

Cross-Domain Few-Shot Writer Adaptation for Real-World Handwritten Mathematical Expression Recognition

arXiv:2609.32513v1 Announce Type: new Abstract: Handwritten mathematical expression recognition (HMER) refers to the task of recognizing and converting handwritten mathematics into a parsable markup l

applicationsarxiv-cs-cv

DCEmbed: Scalable Optimization over Neural Surrogates

arXiv:2609.33879v1 Announce Type: cross Abstract: Neural surrogates can accelerate large-scale optimization by replacing expensive or intractable model components with efficient learned approximations

DEALS: Decentralized Expertise-Aware Load Serving for Multi-Agent LLM Systems

arXiv:2609.33768v1 Announce Type: new Abstract: Multi-agent systems (MAS) have recently emerged as an effective approach for coordinating large language model (LLM)-based agents to solve complex tasks

Deep Epistemic Value Functions for Optimistic Exploration

arXiv:2609.35525v1 Announce Type: new Abstract: Principled exploration in reinforcement learning requires an agent to quantify its epistemic uncertainty and act to resolve it. Uncertainty over the val

Design of Experiment for Discovering Directed Mixed Graph

arXiv:2509.01887v2 Announce Type: replace-cross Abstract: We study the design of interventions for causal discovery in simple structural causal models whose causal graphs are directed mixed graphs (DM

Disciplined Biconvex Programming

arXiv:2511.01813v3 Announce Type: replace-cross Abstract: We introduce disciplined biconvex programming (DBCP), a modeling framework for specifying and solving biconvex optimization problems. Biconvex

Tutorials

Distilling Visual Reasoning into Text Space

arXiv:2609.34408v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have shown strong promise for multimodal reasoning, yet often struggle with tasks requiring concepts beyond what is

tutorialsarxiv-cs-cv

Do Temporal Link Predictors Need Learned Memory? A Smoothed-Count Baseline with a Handful of Parameters

arXiv:2609.35364v1 Announce Type: new Abstract: Many temporal link predictors summarize past interactions through learned node representations. We examine whether simple counts of recurring interactio

Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-based Robots

arXiv:2412.16633v4 Announce Type: replace Abstract: LLM-based robots use Large Language Models (LLMs) as planners to translate natural language instructions into policies such as grasp(), move_to(), a

safetyarxiv-cs-ro

Elucidating the Design Space of Regression-based Diffusion Reinforcement Learning

arXiv:2609.33444v1 Announce Type: cross Abstract: A nascent family of methods that forgoes the policy gradient and reweights a supervised regression instead has garnered momentum in reinforcement lear

safetyarxiv-cs-cv

Enhancing generalization in endwall film cooling prediction: Incorporating the superposition principle into transformer-based neural operators

arXiv:2609.31633v1 Announce Type: new Abstract: In this study, a physics-enhanced neural operator framework is proposed to enhance the generalization prediction ability of the cooling layout of a turb

Equals Money lets customers’ AI tools read data but not move money

Opening a Model Context Protocol server, or MCP server, to customers’ AI tools is becoming standard for fintech companies, but in payments a rogue agent does not just leak data — it moves money. That

agentssiliconangle

F4R: Failure-Driven Recognition, Reconstruction, Refinement, and Redeployment for Continual Robot Self-Improvement

arXiv:2609.35575v1 Announce Type: new Abstract: The real-world performance of current vision-language-action models is fundamentally constrained by the limited coverage of expert demonstrations and th

safetyarxiv-cs-ro

FARE: Deep Reinforcement Learning For Fair Exposure Constrained Uncertainty Aware Financial Content Personalization

arXiv:2609.31890v1 Announce Type: new Abstract: Content personalization systems in financial services must ensure fair exposure across diverse offerings-a requirement driven by contractual obligations

Fast Learning Rate Transfer in Shallow Linear Networks at Growing Training Horizons

arXiv:2609.35029v1 Announce Type: new Abstract: Hyperparameter transfer across model width can substantially reduce the cost of tuning large neural networks, but its behavior when the training horizon

Feedback Makes Perfect: A Closed-Loop Framework for NL-to-STL Translation

arXiv:2609.33287v1 Announce Type: cross Abstract: Signal Temporal Logic (STL) enables rigorous verification and control of cyber-physical systems, but writing correct specifications requires expertise

researcharxiv-cs-ro

Flow-Matching-Based Protein Structure Tokenizer Made Efficient and Easy

arXiv:2609.33129v1 Announce Type: new Abstract: As the bridge between protein modality and discrete modeling, protein structure tokenization still largely relies on heavily engineered training objecti

Focus on Likely Classes for Test-Time Prediction

arXiv:2505.03819v4 Announce Type: replace Abstract: We ask: Can focusing on likely classes of a single, in-domain sample improve accuracy? Prior work argued 'no', we answer 'yes' on average. Standard

ForensicZoom: Adaptive Visual Inspection with Multimodal LLMs for Industrial-Grade Face Forgery Detection

arXiv:2609.31661v1 Announce Type: new Abstract: Reliable face forgery detection is critical to the security of online identity verification systems, where missed attacks compromise security and excess

From Distributions to Stochastic Processes: Neural Approximation of Measure-Valued Maps

arXiv:2609.33649v1 Announce Type: new Abstract: Learning mappings between probability distributions arises naturally when inputs and outputs are represented by populations of samples rather than indiv

From Pixel Generation to Topological Inference: Structural Dual Super-Resolution for Trustworthy Cross-Physical-Domain Trabecular Morphology Learning

arXiv:2609.34716v1 Announce Type: new Abstract: Clinical CT and UHRCT cannot resolve individual trabeculae, whereas synchrotron radiation microCT (SR{mu}CT) provides 3.2{mu}m high-resolution reference

From Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations

arXiv:2609.35375v1 Announce Type: new Abstract: Scaling up robotic manipulation is primarily bottlenecked by the scarcity of real-world robot data. While recent approaches leverage human video demonst

safetyarxiv-cs-ro

Frozen Judges, Moving Agents: Version-Dependent LLM-Judge Error and the Limits of Judge-Assisted Agent Evaluation

arXiv:2609.34198v1 Announce Type: new Abstract: Language-model judges compare agent upgrades with their predecessors, but a fixed judge can make version-dependent mistakes. We analyze 35 public coding

Tutorials

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

arXiv:2609.35341v1 Announce Type: new Abstract: Evaluating semantic similarity between videos is a fundamental challenge in computer vision, essential for tasks ranging from out-of-distribution (OOD)

tutorialsarxiv-cs-cv

Local Ai

Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting

arXiv:2609.35042v1 Announce Type: cross Abstract: Martian weather forecasting is important for future exploration, but atmospheric behaviour on Mars combines spatial, temporal, vertical, and dust-driv

local-aiarxiv-cs-lg

High-Level Text Preprocessing for Semantic Similarity Analysis of Discursive Texts: A Framework and Empirical Demonstration

arXiv:2609.33983v1 Announce Type: cross Abstract: Semantic Textual Similarity (STS) methods assume that a document's lexical content faithfully represents what it asserts. This assumption fails for di

Informative Viewpoint Selection for Episodic-Memory Embodied Question Answering using Omnidirectional Images

arXiv:2609.33288v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires agents to answer natural language questions about surrounding environments from visual observations. In this

agentsarxiv-cs-cv