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Utility Under Attack: Agent Memory Poisoning and the Limits of Content Screening and Provenance Ranking

arXiv:2608.21230v1 Announce Type: cross Abstract: Persistent memory makes false information durable: once a false statement is stored, it can be retrieved into future sessions that match it. We measur

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Model Releases

VA-DPO: Valence-Arousal Direct Preference Optimization for Controllable Emotion Generation in Language Models

DGX agent

arXiv:2608.20374v1 Announce Type: cross Abstract: How precisely can we tell a language model how to feel? Most work on emotional generation answers with a discrete label - happy, angry, sad - which ca

model-releasesarxiv-cs-ai

24 Aug 2026

Hardware

Valid Inference with Synthetic Data via Task Exchangeability

arXiv:2606.13629v2 Announce Type: replace-cross Abstract: There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for

hardwarearxiv-cs-ai

VIALS: A Benchmark for Visual Interpretation of Artifacts in the Life Sciences

arXiv:2608.21357v1 Announce Type: new Abstract: In professional life sciences workflows, scientists routinely interpret visual artifacts (gel blots, microscopy images, plasmid maps, flow cytometry plo

Vibe Coding and Web Application Security: A Twin-Prompt Study

arXiv:2608.20963v1 Announce Type: cross Abstract: Large language models increasingly generate complete web applications from natural-language prompts, raising the question of whether explicitly reques

Vis-Poison: Poisoning Visual Knowledge in Multimodal Retrieval-Augmented Generation

arXiv:2608.20756v1 Announce Type: cross Abstract: While multimodal retrieval-augmented generation (RAG) systems increasingly rely on images as external knowledge sources, the introduction of poisoned

Vision Foundation Model Driven Foreground-Aware Pseudo-LiDAR Generation for Monocular 3D Object Detection

arXiv:2404.09431v3 Announce Type: replace Abstract: Pseudo-LiDAR has become a promising paradigm for monocular 3D object detection by transforming monocular images into point cloud representations tha

researcharxiv-cs-cv

VisTa3D: A Dataset and Benchmark for Thin Object Reconstruction from Vision, Tactile, and 3D Point Clouds

arXiv:2608.20740v1 Announce Type: new Abstract: State-of-the-art 3D reconstruction models, whether from visual, range, or both, tend to underperform on thin objects. This is partially due to the small

ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations

arXiv:2608.21355v1 Announce Type: new Abstract: Recent vision-based action models have demonstrated strong capabilities in complex manipulation, but they rarely leverage explicit object physical prope

safetyarxiv-cs-ro

Volumetric Radiology AI in the Era of Multimodal Large Language Models

arXiv:2608.20549v1 Announce Type: new Abstract: Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward

VortexChat: An agentic framework for autonomous multi-objective integrated photonic design

arXiv:2608.20688v1 Announce Type: new Abstract: The advancement of modern integrated photonics is frequently bottlenecked by device design workflows that rely heavily on manual simulation and expert i

VT-MUSE: Multimodal Unified Sequential Visuotactile Representation Learning for Manipulation

arXiv:2608.21290v1 Announce Type: cross Abstract: We propose VT-MUSE, a Multimodal Unified SEquential representation learning framework for visuotactilemanipulation. Existing approaches often encode v

WA-JEPA: Rethinking the Video JEPA Paradigm for World-Action Modeling in Autonomous Driving

arXiv:2608.20974v1 Announce Type: cross Abstract: Video Joint Embedding Predictive Architecture (V-JEPA) learns powerful spatiotemporal representations from video through self-supervised latent featur

Local Ai

WeedNet: A Foundation Model-Based Global-to-Local AI Approach for Real-Time Weed Species Identification and Classification

arXiv:2505.18930v2 Announce Type: replace-cross Abstract: Early weed identification is crucial for effective management and control, and researchers, agronomists, and technology developers are increas

local-aiarxiv-cs-ai

Weighted Memory Tree: Remembering What Matters for Long-Horizon LLM Agents

arXiv:2608.20631v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated the ability to solve multi-step tasks requiring planning, tool use, and external information access,

What Color Is the Text? A Benchmark for Hallucination Induced by Image-Embedded Prompt

arXiv:2511.13400v3 Announce Type: replace Abstract: We introduce Embedded Stroop, a controlled diagnostic paradigm for measuring image-embedded prompt interference in Multimodal Large Language Models

When Adaptation Hurts: Connecting Representational Drift to OOD Failures in MedSAM Fine-Tuning

arXiv:2608.21300v1 Announce Type: new Abstract: Foundation models for medical image segmentation, like prompt-based MedSAM, generalize well across domains and modalities, often in zero or few-shot set

When Better Teachers Don't Make Better Students: Revisiting Knowledge Distillation for CLIP Models in VQA

model-releasesarxiv-cs-cl

arXiv:2511.17886v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have achieved remarkable success across multimodal tasks, yet their substantial computational demands hinder eff

When Clean Data Hurts: Learning with Monotone Corruptions Beyond Binary Classification

arXiv:2608.20480v1 Announce Type: new Abstract: Optimal learners are tailored to exploit the i.i.d. data assumption underlying the classic PAC model. What if an i.i.d. training sample were corrupted w

researcharxiv-cs-lg

When Do LLMs Replace Fine-Tuned NLU? A Decision Framework for Intent Detection in Production Conversational Systems

arXiv:2608.20371v1 Announce Type: cross Abstract: A common claim is that zero-shot large language models (LLMs) can replace fine-tuned NLU classifiers for intent detection. We test this claim head-to-

When does fusing hand-crafted knowledge with learned representations pay? A cost-normalized benchmark of stacking, substitution, and interference

arXiv:2608.21098v1 Announce Type: new Abstract: Fusing prior knowledge with data-driven learning is attractive where data is scarce, yet no controlled account says when it helps, is redundant, or harm

When Failures Propagate: Causal Failure Attribution in Agentic Retrieval-Augmented Generation

arXiv:2608.20627v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves retrieval, reasoning, and answer generation across multiple hops. A retrieval error at hop 1

When Generated Images Look Right and Retrieve Wrong: Coverage-Guided Cross-Scale Re-Indexing for Knowledge-Faithful Generative Perception

arXiv:2608.20810v1 Announce Type: cross Abstract: Multimodal information systems increasingly route generated visual content back through the same vision-language index that informed its production, s

When Graph-JEPA Learns the Wrong Thing: Diagnosing and Repairing Category-Conditional Collapse

arXiv:2608.20516v1 Announce Type: new Abstract: Joint-embedding predictive architectures are selected almost universally by linear probing and effective rank. We report a case where both read healthil

researcharxiv-cs-lg

When Looks Do Not Lie: Discourse Structure Guided In-Context Learning for Faithful Diagram Generation

arXiv:2601.20476v2 Announce Type: replace Abstract: GenAI is widespread in educational applications; however, it is known to generate content with intrinsic and extrinsic hallucination. We introduce a

researcharxiv-cs-cl

When Retrieval Fails Before It Begins: Structurally Indirect Prerequisite Eviction as a Retention Failure in Agentic Memory

arXiv:2608.20400v1 Announce Type: new Abstract: Agentic memory under a fixed budget involves two stages: retention and retrieval. Existing retrieval-centered paradigms implicitly assume necessary evid

When the Feature Pool Goes Algorithmic: Extending Mufwene's Ecology of Language Evolution to LLM-Mediated Exposure

arXiv:2608.21088v1 Announce Type: new Abstract: Mufwene's ecological model locates language evolution in competition among variants contributed by individual idiolects and in speakers' selection from

researcharxiv-cs-cl

When to Ponder: Adaptive Compute Allocation for Code Generation via Test-Time Training

arXiv:2601.00894v2 Announce Type: replace-cross Abstract: Large language models apply uniform computation to all inputs, regardless of difficulty. We propose PonderTTT, a gating strategy using the TTT

researcharxiv-cs-cl

When Trust Meets Truth: Trust-Truth Separability in LLM-as-Judge

arXiv:2608.21097v1 Announce Type: new Abstract: LLM-as-Judge systems can produce multi-dimensional evaluations, such as trustworthiness, reliability, and factuality, and these outputs are often interp

researcharxiv-cs-ai

When Vocabulary Comprehension Fails Clinical Reasoning: Evaluating Therapy Bots' Safety Risks for Generation Alpha

arXiv:2608.20345v1 Announce Type: cross Abstract: Conversational AI systems have become informal mental health support resources for Generation Alpha (Gen Alpha, born 2010-2024), with 13.1% of U.S. ad

When Words Are Safe But Actions Kill: Probing Physical Jailbreak Beyond Textual Jailbreak in Hidden-State Risk Space

arXiv:2607.15218v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly serve as high-level planners for embodied agents, where linguistically benign instructions can become unsa

Who Delegates to AI? Evidence from 53,000 Agent Configurations

arXiv:2608.20425v1 Announce Type: new Abstract: A growing literature measures how far occupations are exposed to AI, but these measures capture where AI could perform tasks, not whether workers have a

Who Do Language Models Think Is Competent? A Mechanistic Analysis of Occupational Bias

arXiv:2608.20347v1 Announce Type: cross Abstract: Language models (LMs) often pass behavioral bias evaluations, but it remains unclear whether they no longer represent the underlying associations that

Why2Speak: Faithful Reasoning for Abstaining Action Policies

arXiv:2608.20670v1 Announce Type: new Abstract: Many agentic systems must repeatedly choose between acting and abstaining, making faithful reasoning important for oversight: an explanation is useful o

WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition

arXiv:2608.21281v1 Announce Type: new Abstract: Recent advances in field technology have led to a massive influx of in-the-wild video data for ecological science. The primary bottleneck in leveraging

World models of environment, agent and joint agent-environment systems

arXiv:2608.20401v1 Announce Type: new Abstract: World models are a central component of model-based reinforcement learning. They are usually discussed in terms of what variables they predict, such as

WorldLines: Benchmarking and Modeling Long-Horizon Stateful Embodied Agents

arXiv:2606.18847v2 Announce Type: replace Abstract: To assist humans over extended periods in real homes, embodied agents must remember user routines, world states, and past interactions. Existing lon

Wrong-Physics Backdoors in Neural PDE Operators

model-releasesarxiv-cs-lg

arXiv:2608.20439v1 Announce Type: new Abstract: Neural PDE operators are increasingly trained on reusable solver archives, yet validation often relies on clean prediction error and parameter-agnostic

Z^2-ACT: End-to-End Verifiable Agentic Intent Control for Open 6G RAN

arXiv:2608.21049v1 Announce Type: cross Abstract: With the progression in open and disaggregated 6G radio access networks, it is expected that the system will be able to host multi-vendors. In order t

Local Ai

Zero-Shot Color Image Manipulation Localization via Noise Residual Artifact Pattern Analysis

arXiv:2608.20558v1 Announce Type: new Abstract: Digital cameras embed device-specific artifacts into every acquired image through demosaicing, in-camera post-processing, and lossy compression. These t

local-aiarxiv-cs-cv

4DAnyone: Create Anyone in 4D from a Casual Monocular Video

arXiv:2608.20335v1 Announce Type: new Abstract: We present 4DAnyone, a framework for reconstructing 4D humans from an uncalibrated monocular video by generating reconstruction-grade multiview-consiste

researcharxiv-cs-cv

A 360-Degree Vision Dataset for Learning Yaw Control on GPS-Denied Micro-UAVs in Disaster-Response-Relevant Environments

arXiv:2608.19866v1 Announce Type: new Abstract: This paper presents a novel data-driven approach to camera-based autonomy for micro-drones in GPS-denied, radio-challenging indoor environments. The tar

agentsarxiv-cs-cv

Applications

A comparison between ceiling-mounted FMCW, IR-UWB and Wi-Fi radar for in-bedroom human activity monitoring and sleep interruption detection

arXiv:2608.20322v1 Announce Type: new Abstract: Despite their growing importance for contact-free radio frequency (RF) based healthcare monitoring, different radio technologies such as frequency-modul

applicationsarxiv-cs-lg

A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries

arXiv:2608.19875v1 Announce Type: cross Abstract: Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropria

A Layered Simplex Architecture for Large Alphabets

model-releasesarxiv-cs-lg

arXiv:2608.19908v1 Announce Type: cross Abstract: Probability estimation over large alphabets under log loss is a well-studied problem, with celebrated methods such as the Good-Turing estimator. We in

Local Ai

A Locally Tokenized Generative Model for Robust Time-Series Watermarking

arXiv:2608.19727v1 Announce Type: cross Abstract: Watermarking is a central tool for provenance in generative models, yet its application to multivariate time series remains hindered by reliability fa

local-aiarxiv-cs-ai

A Physics-Informed Neural Network Approach for UAV Path Planning in Dynamic Environments

arXiv:2510.21874v2 Announce Type: replace-cross Abstract: Unmanned aerial vehicles (UAVs) operating in dynamic wind fields must generate safe and energy-efficient trajectories under physical and envir

A Plug-in Interpretation of Conditioning in Score-Based Diffusion Models

arXiv:2608.19504v1 Announce Type: new Abstract: We propose a conditioning mechanism for diffusion models based on multi-speed joint diffusion of the target and the condition. The mechanism learns an u

researcharxiv-cs-cv