Search: “models”

Zero-OVCD: Bridging Training-Free Foundation Models and Pseudo-Label Learning for Open-Vocabulary Change Detection

arXiv:2608.11663v1 Announce Type: new Abstract: Open-vocabulary change detection (OVCD) enables the identification of user-specified land-cover changes in bitemporal remote sensing images, but existin

13 Aug 2026

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Actionable Hallucination Detection: Translating Latent Uncertainty into Agentic Critique

DGX agent

arXiv:2608.10430v1 Announce Type: cross Abstract: Large Language Models (LLMs) deployed as AI agents frequently exhibit user specification-grounding failures, executing hallucinated, undesired actions

model-releasesarxiv-cs-ai

12 Aug 2026

Actions Speak Louder than Words: Measuring Cross-Lingual Policy Retention in Tool-Using Agents

arXiv:2608.11110v1 Announce Type: new Abstract: When a tool-using agent is given the same task in a different language, does it still take the same steps? Multilingual evaluation rarely asks: it compa

safetyarxiv-cs-cl

Cracks in the Foundation: Seemingly Minor Architectural Choices Impact Long Context Extension

arXiv:2608.10296v1 Announce Type: new Abstract: One might imagine that architectural variations within the dense transformer paradigm have a limited effect on accuracy. However, we demonstrate that th

Data Attribution of Emergent Misalignment with Persona Features

arXiv:2608.11025v1 Announce Type: new Abstract: Emergent misalignment (EM) is the phenomenon where fine-tuning a language model on a narrow task leads to harmful behavior in unrelated domains. A leadi

safetyarxiv-cs-cl

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

arXiv:2608.10954v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates signif

Is This Your Final Answer? Cross-Contextual Consistency as a Measure of LLM Credibility

arXiv:2608.10315v1 Announce Type: cross Abstract: Large language models (LLMs) are powerful black-box systems, making it difficult to discern whether their answers reflect stable internal beliefs or s

Local Ai

JEPA-WAM: Stage-Level Joint-Embedding Prediction for World-Action Models in Robot Manipulation

arXiv:2608.10780v1 Announce Type: new Abstract: Generalist robot policies aim to map multimodal observations and linguistic task instructions to actions across diverse tasks. However, existing methods

local-aiarxiv-cs-ro

Longitudinal 3D Foundation Modeling for Neoadjuvant Breast Cancer Response Prediction from Serial DCE-MRI

arXiv:2608.09991v1 Announce Type: cross Abstract: Pathologic complete response (pCR) is an important endpoint in neoadjuvant chemotherapy (NAC) for breast cancer, and predicting pCR from imaging durin

MemSpec: Memory-Aware Runtime for Adaptive Draft Scheduling in Speculative Decoding on Edge Devices

arXiv:2608.10362v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to speculate multiple tokens,

researcharxiv-cs-ai

myMediWhisper: Construction of Burmese Medical Speech Corpus and Whisper Fine-Tuning for Clinical Dialogue ASR

arXiv:2608.11036v1 Announce Type: new Abstract: Although Whisper models benefit from large-scale multilingual pre-training, their performance on Burmese medical speech remains limited. This work prese

Nonlinear Model Predictive Control via Sequential Convex Programming for Drone-to-Drone Docking

arXiv:2608.10542v1 Announce Type: new Abstract: Autonomous mid-air docking of multi-rotor vehicles under disturbance-driven target motion poses a constrained non-linear trajectory optimization challen

agentsarxiv-cs-ro

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign

arXiv:2502.02068v3 Announce Type: replace-cross Abstract: This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid int

researcharxiv-cs-cl

Status Association Does Not Reliably Predict Decision Leakage

arXiv:2608.10089v1 Announce Type: cross Abstract: Bias evaluations often move too quickly from evidence that a model encodes a social association to claims that the same association will alter consequ

safetyarxiv-cs-ai

Stream Forcing: Constructing Unified Training Trajectory for Robust Streaming Video Generation

model-releasesarxiv-cs-cv

arXiv:2608.10439v1 Announce Type: new Abstract: Streaming video generation holds strong potential for world modeling, where future frames must be inferred online sequentially to form a continuous vide

Toward a Theory of Value in AI Alignment

arXiv:2608.10327v1 Announce Type: new Abstract: Can AI systems be aligned to human values? The popularization of large language models (LLMs) and multi-modal foundation models has seen a rise in harms

safetyarxiv-cs-ai

Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data

arXiv:2608.11022v1 Announce Type: cross Abstract: Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their con

Calib3R: Hand-Eye Calibration and 3D Metric-Scaled Scene Reconstruction with 3D Foundation Models

arXiv:2509.08813v2 Announce Type: replace Abstract: Robots often rely on RGB images for tasks like manipulation. However, reliable interaction typically requires a 3D scene representation that is metr

researcharxiv-cs-ro

Can Webcam Gaze Constrain Mesa-Objectives in Driving Models? An Instrument Precision Analysis

arXiv:2608.08947v1 Announce Type: new Abstract: Current hazard detection systems in autonomous driving may develop mesa objectives, learned internal goals that achieve high training performance throug

agentsarxiv-cs-cv

Local Ai

Classical SU(2) Models Match or Exceed Shallow Variational Quantum Circuits on Vision Benchmarks

arXiv:2608.07822v1 Announce Type: cross Abstract: Quaternion-valued neural networks and variational quantum circuits (VQCs) both derive local transformations from SU(2) geometry, yet their performance

local-aiarxiv-cs-lg

CuteTTS: Efficient and High-Quality Speech Synthesis via Autoregressive Modeling of Continuous Latents

arXiv:2608.08638v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) now supports interactive assistants, personalized media, and accessibility tools. All TTS systems require faithful ling

researcharxiv-cs-ai

Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging

arXiv:2608.08926v1 Announce Type: new Abstract: Neuroimaging and genetic testing are two important clinical references for nervous system diseases, offering complementary diagnostic information. Howev

researcharxiv-cs-ai

DINO-3DRA: Leveraging 2D Foundation Model Semantics for 3D Cerebral Aneurysm Segmentation

arXiv:2608.07767v1 Announce Type: new Abstract: Accurate aneurysm segmentation in 3D rotational angiography (3DRA) is hindered by extreme class imbalance, morphological similarity to vessels, and abse

DS@GT ARC at Touche: Large Language Models for Retrieval-Augmented Debate

arXiv:2608.08143v1 Announce Type: cross Abstract: We extend the DS@GT ARC working-note submission to the Touche 2025 Retrieval-Augmented Debate task. The task has two subtasks: generating the next utt

researcharxiv-cs-cl

Emotion2Skill: Model-Internal Emotion Signals for Adaptive Skill Selection and Evolution

arXiv:2608.09248v1 Announce Type: new Abstract: Skill-based LLM agents select reusable procedures from an external library to solve complex tasks, yet their routing decisions rely entirely on text-lev

agentsarxiv-cs-ai

FreSH: Frequency-Segmented Hierarchical Multi-Expert Framework for Multivariate Time Series Classification

arXiv:2608.08207v1 Announce Type: cross Abstract: Multivariate Time Series Classification (MTSC) demands models that can effectively capture complex temporal patterns across multiple scales while rema

From Prompt to Harness: Coderlet from Scratch

arXiv:2608.09480v1 Announce Type: new Abstract: A model alone does not determine how a programming agent acts. What the model sees, how actions enter the environment, how feedback returns, and how one

agentsarxiv-cs-ai

Tutorials

Generative Models: Principles, Architectures, and Applications

arXiv:2608.08101v1 Announce Type: new Abstract: Generative AI has emerged as one of the most transformative forces in modern artificial intelligence, reshaping how we create, imagine, and interact wit

tutorialsarxiv-cs-ai

Gradient Under Microscope: Benchmarking Resource Utilization of Memory-Efficient Gradient Computation Methods

model-releasesarxiv-cs-lg

arXiv:2608.08961v1 Announce Type: new Abstract: AI training's rising resource intensity is straining electricity supplies and carbon budgets, motivating systematic study of memory-efficient training o

Impact of Dataset Composition on Embedded Real-Time UAV Wildfire Detection Using Compact YOLO Models

arXiv:2608.07554v1 Announce Type: new Abstract: The development of vision-based wildfire detection systems for unmanned aerial vehicles is constrained by the limited availability of diverse real-world

safetyarxiv-cs-cv

LogicIF: Towards Complex Logic Instruction Following

arXiv:2508.09125v4 Announce Type: replace Abstract: Instruction following has catalyzed the recent era of Large Language Models (LLMs) and is the foundational skill underpinning more advanced capabili

Applications

Mask-aware inference with State-Space Models

arXiv:2603.04568v2 Announce Type: replace Abstract: Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For

applicationsarxiv-cs-cv

MultiShadow: Multi-Object Shadow Generation for Image Compositing via Diffusion Model

arXiv:2603.02743v4 Announce Type: replace Abstract: Realistic shadow generation is crucial for achieving seamless image compositing, yet existing methods primarily focus on single-object insertion and

safetyarxiv-cs-cv

Out-of-Distribution Federated Distillation with Domain-Aware Proxy

model-releasesarxiv-cs-lg

arXiv:2608.08525v1 Announce Type: new Abstract: Federated Learning is a distributed machine learning paradigm that trains a global model by aggregating local clients without sharing private data of ea

Proxy OPD: On-Policy Distillation with Transferable Relative Proxy Update

arXiv:2607.11505v2 Announce Type: replace-cross Abstract: Post-training for large language models typically couples policy exploration with model optimization, hindering the reuse of high-reward behav

safetyarxiv-cs-ai

Real Data Closes Synthetic-to-Real Gap in Optical Chemical Structure Recognition

model-releasesarxiv-cs-cv

arXiv:2608.09100v1 Announce Type: cross Abstract: Millions of chemical structures appear in patents and papers only as drawings, and using that information at scale requires reading the drawings. OCSR

Reproducing and Stress-Testing Two Approaches to LLM Reasoning Reliability: Test-Time Probability Aggregation and Logic-Representation Editing

arXiv:2608.08514v1 Announce Type: new Abstract: We independently reproduce two recent methods for making large language model (LLM) reasoning more reliable, and stress-test them across domains and mod

Local Ai

Scale-to-Dialogue: Low-Burden Elicitation of Daily Premenstrual Symptom Ratings with Small Language Models

arXiv:2608.08746v1 Announce Type: new Abstract: Prospective daily symptom tracking is central to premenstrual health assessment, but repeated ordinal forms impose substantial response burden. We formu

local-aiarxiv-cs-ai

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

arXiv:2608.09885v1 Announce Type: new Abstract: The safety of large language model (LLM) agents depends not only on model weights but also on the agent harness that manages context, memory, tools, per

Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents

arXiv:2601.18077v3 Announce Type: replace Abstract: Cooperative reasoning under incomplete information remains challenging for both humans and multi-agent systems. The card game Hanabi embodies this c

Stateful CARS: Exact Cross-History Reuse for Policy-Constrained LLM Agents

model-releasesarxiv-cs-lg

arXiv:2608.08282v1 Announce Type: new Abstract: Tool-using language-model agents face constraints whose meaning changes with observations and prior actions. We study exact sampling from the model dist

STEMMA: An Adversarial Multi-Agent Framework for Evaluating Self-Identity Consistency in LLMs

arXiv:2608.08164v1 Announce Type: cross Abstract: Knowledge Distillation is a widely adopted technique in the training and fine-tuning of large language models (LLMs) enabling transfer of structured i

agentsarxiv-cs-ai

SUMI: Scalable Unified Model for 3D Point Cloud Inference

arXiv:2608.08115v1 Announce Type: new Abstract: Point cloud completion commonly follows a coarse-to-fine paradigm, where a low-density coarse shape is first predicted and then upsampled to the target

SynVAR: Synergizing Spatial and Semantic Alignment in Visual Autoregressive Model

arXiv:2608.07948v1 Announce Type: new Abstract: VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling comp

safetyarxiv-cs-cv

Think Deep, Speak Once: Relit, A Recursive Latent Implicit Transformer Framework

arXiv:2608.08113v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has become the dominant paradigm for eliciting reasoning in Large Language Models (LLMs), yet it creates substantial co

To Memorize or to Retrieve: Scaling the Interaction Between Pretraining and Retrieval

arXiv:2604.00715v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) improves language model (LM) performance by providing relevant context at test time for knowledge-intensi

Wiener Representation Filtering for VLM Hallucination Suppression

model-releasesarxiv-cs-cv

arXiv:2608.08167v1 Announce Type: new Abstract: Vision-language models (VLMs) excel at open-ended captioning and visual QA but often describe objects, attributes, or relations absent from the image, a

A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

arXiv:2608.06694v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics extends polymer simulation beyond the scales accessible to all-atom (AA) methods, but bottom-up CG modeling is la