Search: “models”

SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification

arXiv:2607.13081v1 Announce Type: cross Abstract: We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive informati

16 Jul 2026

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Model Releases

Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection

DGX agent

arXiv:2607.13452v1 Announce Type: cross Abstract: Incremental object detection (IOD) aims to extend detectors to new categories while retaining previously acquired knowledge. Existing methods often ad

model-releasesarxiv-cs-ai

16 Jul 2026

TRACE: Turn-level Reward Assignment via Credit Estimation for Long-Horizon Agents

model-releasesarxiv-cs-lg

arXiv:2607.13988v1 Announce Type: new Abstract: Multi-turn agents solve complex tasks through extended sequences of tool interactions before producing a final answer, making credit assignment a fundam

16 Jul 2026

ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory

model-releasesarxiv-cs-ro

arXiv:2607.10350v1 Announce Type: cross Abstract: Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime la

An Agentic AI Scientific Community for Automated Neural Operator Discovery

model-releasesarxiv-cs-lg

arXiv:2607.12122v1 Announce Type: new Abstract: We present an agentic approach to autonomous neural operator discovery based on an AI scientific community, which consists of a swarm of virtual laborat

AutoTrace: From Patches to Triggers via Agentic Interprocedural Exploration

arXiv:2607.12058v1 Announce Type: cross Abstract: Given a vulnerability-fixing commit, trigger localization asks which specific statement turns the vulnerable program state into a concrete unsafe oper

Beyond Logit Adjustment: A Residual Decomposition Framework for Long-Tailed Reranking

arXiv:2604.01506v2 Announce Type: replace Abstract: Long-tailed classification, where a small number of frequent classes dominate many rare ones, remains challenging because models systematically favo

CASHEW: Stabilizing Multimodal Reasoning via Iterative Trajectory Aggregation

arXiv:2601.08010v3 Announce Type: replace Abstract: Vision-language models achieve strong performance across a wide range of multimodal understanding and reasoning tasks, yet their multi-step reasonin

safetyarxiv-cs-cv

Constructed Reality, Contested Priors: Decoupling and the Architecture of Cognitive Relapse Under the Free Energy Principle

arXiv:2607.11958v1 Announce Type: new Abstract: Under the free energy principle, a predictive system does not observe reality directly; it maintains a generative model of the world and experiences tha

DeepTravel: An End-to-End Agentic Reinforcement Learning Framework for Autonomous Travel Planning Agents

arXiv:2509.21842v2 Announce Type: replace Abstract: Travel planning (TP) agent has recently worked as an emerging building block to interact with external tools/resources for travel itinerary generati

Diagrams-to-Dynamics (D2D): Exploring Causal Loop Diagram Leverage Points under Uncertainty

arXiv:2508.05659v4 Announce Type: replace Abstract: Background: Causal loop diagrams (CLDs) are widely used in health and environmental research to represent hypothesized causal structures underlying

Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?

arXiv:2607.12462v1 Announce Type: new Abstract: Existing traffic forecasting models commonly focus on extracting spatial dependencies, particularly global spatial information, which characterizes the

researcharxiv-cs-ai

Dynamic Online Processor-Native Inference for State Estimation

arXiv:2607.12095v1 Announce Type: cross Abstract: Sensor-rich data-driven applications increasingly use Bayesian approaches to infer latent states of dynamic systems from noisy sensor measurements and

Enabling 24-hour Agricultural Robotics: Unsupervised Day-to-Night Cross-Modal Image Translation for Nighttime Visual Navigation

arXiv:2607.12065v1 Announce Type: cross Abstract: While visual navigation has been extensively studied in agricultural robotics, most existing systems assume daytime conditions. In fact, deploying aut

ExToken: Structured Exploration for Efficient Vision-Language-Action Reinforcement Fine-tuning

arXiv:2607.12931v1 Announce Type: new Abstract: Reinforcement Learning (RL) has demonstrated significant potential for improving Vision-Language-Action (VLA) models on complex manipulation tasks. Howe

safetyarxiv-cs-ro

Extractable Memorization From First Principles

arXiv:2607.12649v1 Announce Type: cross Abstract: Recent work on extractable memorization in LLMs suffers from two contrasting validity problems. Some studies overstate extraction, e.g., relying on se

Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention

arXiv:2505.16157v2 Announce Type: replace Abstract: Transformer-based models have made remarkable progress in image restoration (IR) tasks. However, the quadratic complexity of self-attention in Trans

researcharxiv-cs-cv

Agents

Fin-Analyst at FinMMEval 2026 Task 3: A Live Hybrid Trading Agent with LLM Specialists and Rule-Based Signals

arXiv:2607.12233v1 Announce Type: cross Abstract: Large language model (LLM) trading agents show promising performance in equity markets, yet remain narrowly focused on US equities with little evidenc

agentsarxiv-cs-ai

GAINS: Gaussian-based Inverse Rendering from Sparse Multi-View Captures

arXiv:2512.09925v2 Announce Type: replace Abstract: Recent advances in Gaussian Splatting-based inverse rendering extend Gaussian primitives with shading parameters and physically grounded light trans

High-Dimensional Gaussian Mean Estimation under Realizable Contamination

arXiv:2603.16798v2 Announce Type: replace Abstract: We study mean estimation for a Gaussian distribution with identity covariance in R^d under a missing data scheme termed realizable epsilon-contamina

Let RGB Be the Language of Vision

arXiv:2607.12450v1 Announce Type: new Abstract: This work introduces a unified formulation for vision models, where diverse forms of visual information beyond natural images, such as masks, depth maps

researcharxiv-cs-cv

Tutorials

QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design

arXiv:2607.11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in com

tutorialsarxiv-cs-ai

Applications

ReflectWorld-MM: An Entity-Oriented Multimodal Memory System for Open-Ended Video Streams

arXiv:2607.09759v2 Announce Type: replace-cross Abstract: Building assistants that can continually watch the world, remember what they see, and reason over their accumulated experience is a long-stand

applicationsarxiv-cs-ai

SeqGPT: A Constrained Transformer Agent for the Inverse Designof Multi-Panel Composite Structures

arXiv:2607.11910v1 Announce Type: cross Abstract: Optimizing composite stacking sequences to match continuous targets (e.g., Lamination or Buckling Parameters) with discrete manufacturing constraints

Local Ai

Toward Production-Ready Federated Learning in Healthcare: Privacy, Orchestration, and Governance in MLOps

arXiv:2607.10467v2 Announce Type: replace-cross Abstract: Healthcare organizations often cannot freely centralize patient data because medical records are sensitive, regulated, and institutionally con

local-aiarxiv-cs-lg

Transforming LLMs into Efficient Cross-Encoders via Knowledge Distillation for RAG Reranking

arXiv:2607.11933v1 Announce Type: new Abstract: Cross-encoders achieve high reranking accuracy in Retrieval-Augmented Generation (RAG) pipelines but impose quadratic inference costs that limit real-ti

TrustVLA: Mechanism-Guided Inference-Time Defense Against Vision-Language-Action Backdoors

arXiv:2607.12571v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are deployed through pipelines that end users cannot audit, and a poisoned VLA can behave normally on clean observat

safetyarxiv-cs-ro

UniVR: Thinking in Visual Space for Unified Visual Reasoning

arXiv:2607.12800v1 Announce Type: new Abstract: Learning broad world knowledge directly from raw visual data is a fundamental capability of intelligence. We introduce UniVR, the first investigation in

ViHoRec: A Quality-Controlled Vietnamese Hotel Recommendation Dataset and Cold-Start Benchmark

arXiv:2607.12946v1 Announce Type: cross Abstract: Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a res

Can We Trust LLM's Logic? Quantifying Uncertainty, Coherence, and Robustness via a Graph-Based Framework

arXiv:2607.08017v1 Announce Type: cross Abstract: Large-Language Models (LLMs) can be prone to flawed and unfaithful reasoning that decoding strategies like Self-Consistency (SC) fail to detect as the

researcharxiv-cs-ai

Classifier Chain-based Pathological Test Recommendation

arXiv:2607.08299v1 Announce Type: new Abstract: Accurate and timely diagnoses are essential for quality patient care. However, delayed recommendation of diagnostic tests and physicians' subjective int

Cross-seed explainability using Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders

arXiv:2607.08499v1 Announce Type: new Abstract: We present a Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoder (SAE) for extracting cross-seed universal features from independently trai

CT-CLIP Representations for Multimodal Lung Cancer Survival Prediction

arXiv:2607.08503v1 Announce Type: new Abstract: Accurate prognosis prediction is important for treatment planning in lung cancer, but deep learning-driven survival modelling is often limited by the sc

researcharxiv-cs-cv

Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

arXiv:2607.08208v1 Announce Type: new Abstract: This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system co

Agents

From Triggers to Emotions: A CPM-Grounded Appraisal Multi-Agent for Dynamic Emotional Evolution in Persona-Based Dialogue

arXiv:2607.07824v1 Announce Type: cross Abstract: Large Language Models (LLMs) have substantially advanced persona-based dialogue agents for emotion-sensitive role simulation in healthcare, education,

agentsarxiv-cs-ai

Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction

arXiv:2607.08769v1 Announce Type: new Abstract: Scaling 3D Gaussian Splatting (3DGS) to large outdoor scenes is costly in both data acquisition and computation. Adopting panoramic images with equirect

LlamaSeg: Image Segmentation via Autoregressive Mask Generation

arXiv:2505.19422v2 Announce Type: replace Abstract: We present extbf{LlamaSeg}, a visual autoregressive framework that unifies multiple image segmentation tasks via natural language instructions. By r

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro

safetyarxiv-cs-ai

MetaHGNIE: Meta-Path Induced Hypergraph Contrastive Learning in Heterogeneous Knowledge Graphs

arXiv:2512.12477v2 Announce Type: replace Abstract: Estimating node importance in heterogeneous knowledge graphs is a fundamental problem underlying recommendation, search, and knowledge decision syst

Applications

On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting

arXiv:2607.08250v1 Announce Type: new Abstract: Dynamic scene reconstruction remains challenging due to the heterogeneous and spatially varying nature of real-world motion. Although recent 3D Gaussian

applicationsarxiv-cs-cv

PhasorFlow: A Python Library for Unit Circle Based Computing

arXiv:2603.15886v3 Announce Type: replace-cross Abstract: We present PhasorFlow, an open-source Python library for computing on the S^1 unit circle. Inputs are encoded as complex phasors z=e^{iphi} on

Hardware

SLORR: Simple and Efficient In-Training Low-Rank Regularization

arXiv:2607.08754v1 Announce Type: cross Abstract: Low-rank factorization is widely used to compress neural networks, but modern models are often not naturally amenable to aggressive factorization with

hardwarearxiv-cs-ai

SwinIFS: Landmark Guided Swin Transformer For Identity Preserving Face Super Resolution

arXiv:2601.01406v2 Announce Type: replace-cross Abstract: Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to

Applications

The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs

arXiv:2607.08734v1 Announce Type: new Abstract: Post-training quantization is widely used to deploy large language models in resource-constrained settings, yet its evaluation relies almost exclusively

applicationsarxiv-cs-ai

UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech

arXiv:2508.09767v3 Announce Type: replace-cross Abstract: We propose UtterTune, a lightweight method for adapting a multilingual text-to-speech (TTS) system built on a large language model (LLM). It i

researcharxiv-cs-cl

Validating LLMs in social science: Epistemic threats and emerging norms

arXiv:2607.07915v1 Announce Type: cross Abstract: Large language models (LLMs) are reshaping social science methodology. Researchers increasingly prompt language models to generate quantitative measur

safetyarxiv-cs-cl

VSRo-200: A Romanian Visual Speech Recognition Dataset for Studying Supervision and Multimodal Robustness

arXiv:2607.08112v1 Announce Type: new Abstract: We introduce VSRo-200, the first large-scale dataset for visual speech recognition (lip reading) in Romanian, comprising 200 hours of real-world podcast

What LLM Forecasters Know but Don't Say: Probing Internal Representations for Calibration and Faithfulness

arXiv:2607.08046v1 Announce Type: cross Abstract: Large language models fine-tuned for forecasting can be accurate yet poorly calibrated, and their chain-of-thought (CoT) reasoning may not faithfully

researcharxiv-cs-ai