Search: “benchmark”

DetAug: Obstacle-Blind Trajectory Augmentation for Zero-shot Obstacle Avoidance

arXiv:2609.18395v1 Announce Type: new Abstract: Policies for robotic manipulation are produced by training on large teleoperated datasets. These datasets typically consist of free-space trajectories,

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Research

Disentangling Long-Term Memory via Latent Neuro-Symbolic Reasoning

DGX agent

arXiv:2609.18461v1 Announce Type: new Abstract: Personalized agents are required to reason over long-term history interactions to infer both explicit preferences and implicit behavioral evidence. Whil

researcharxiv-cs-ai

17 Sept 2026

DISTA-Net++: Rethinking Infrared Small Target Unmixing Beyond Sub-Pixel Separation

arXiv:2609.18773v1 Announce Type: new Abstract: Long-range infrared imaging frequently confronts dense target clusters whose diffraction-limited signatures merge into a single indistinguishable blob,

DistAL: Distance-based Advantage Learning for VLA Fine-Tuning

arXiv:2609.18392v1 Announce Type: new Abstract: Vision-language-action models (VLAs) have trans- formed the field of robotic manipulation in recent years by combining the semantic understanding of LLM

safetyarxiv-cs-ro

Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models

arXiv:2412.16555v4 Announce Type: replace Abstract: Large language models (LLMs) are widely applied in various fields of society due to their powerful reasoning, understanding, and generation capabili

Tutorials

Dose-Aware Cold Diffusion with Physics Consistency for Generalizable Low-Dose CT Reconstruction

arXiv:2609.18943v1 Announce Type: cross Abstract: Reducing radiation dose in computed tomography significantly degrades image quality and poses challenges for accurate and clinically reliable reconstr

tutorialsarxiv-cs-ai

Tutorials

DR.WILSS: Diffusion-Based Replay for Weakly Supervised Continual Semantic Segmentation

arXiv:2609.18444v1 Announce Type: new Abstract: Weakly supervised class-incremental semantic segmentation (WILSS) aims to train a segmentation model over multiple steps, each introducing new concepts

tutorialsarxiv-cs-cv

ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control

arXiv:2609.19080v1 Announce Type: new Abstract: As robot capabilities increase, quadratic programming (QP)-based controllers must account for a similarly increasing number of constraints to ensure saf

researcharxiv-cs-ro

Evidence-Grounded Agentic Formulation Development in an Autonomous Laboratory

arXiv:2609.19099v1 Announce Type: new Abstract: Self-emulsifying drug delivery systems (SEDDS) can improve the oral bioavailability of poorly soluble drugs, but identifying high-performing formulation

Evolving Error States: Failure-Aware Progressive Repair for Ultrasound Lesion Segmentation

arXiv:2609.18256v1 Announce Type: new Abstract: Reliability under sparse and heterogeneous failures remains a fundamental challenge for medical image segmentation. High average accuracy can conceal a

researcharxiv-cs-cv

Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge Evaluation Plan

arXiv:2609.17913v1 Announce Type: new Abstract: Face--voice association models may rely on language or gender cues in the voice rather than on speaker-specific voice characteristics, which can lead to

Faking Good and Faking Bad in LLMs: Response Distortion Across Dark Triad Personality Traits

arXiv:2609.17534v1 Announce Type: new Abstract: Social desirability and impression management are pervasive sources of response distortion in human personality assessment, yet their effects on Large L

safetyarxiv-cs-cl

Local Ai

First Token Matters: Understanding Safety Collapse in Large Reasoning Models

arXiv:2609.18471v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) exhibit strong problem-solving abilities, yet their safety alignment often degrades when handling harmful queries. Existin

local-aiarxiv-cs-ai

FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory

arXiv:2609.18623v1 Announce Type: cross Abstract: State-of-the-art vision-language-action models (VLA) for autonomous driving face critical limitations: excessive parameter counts, inefficient high-re

FoundAna: A GNN-assisted Foundation Model for Graph Anomaly Detection

arXiv:2609.18107v1 Announce Type: new Abstract: Graph anomaly detection aims to identify graph structures (e.g., nodes, edges, or subgraphs) that deviate significantly from expected patterns, which su

FRAUDSkill: Structured Frozen-Weight Skill Optimization for Audio Anti-Fraud Detection

arXiv:2609.18766v1 Announce Type: cross Abstract: Large audio-language models have shown promise for anti-fraud detection by directly processing speech and reasoning over fraud-related evidence. Their

FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing

arXiv:2512.22143v2 Announce Type: replace-cross Abstract: Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communicatio

Geometry-Driven Shadow Harmonisation for Composited Faces: A Multiplicative, Albedo-Preserving Relighting Pipeline

arXiv:2609.17740v1 Announce Type: new Abstract: Face swapping and face compositing pipelines routinely produce a face that is geometrically well aligned but photometrically implausible: the donor face

GraphEcho: Structural Redundancy and Evidence Provenance in LLM Graph Agents

arXiv:2609.17695v1 Announce Type: new Abstract: A large language model (LLM) agent can follow more graph paths without acquiring more independent evidence. GraphEcho tests whether agents mistake these

GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation

arXiv:2609.18358v1 Announce Type: new Abstract: Robot manipulation policies often struggle to generalize beyond their demonstrations, even when new instructions involve familiar objects and behaviors.

Higher-order pruning of experts in mixture-of-experts language models

arXiv:2609.18916v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models suffer from large parameter counts, which create a significant memory bottleneck. Expert pruning is the most

HiLNO: A Hierarchical Latent Neural Operator with Multi-Scale Supervision for PDEs on General Geometries

arXiv:2609.18419v1 Announce Type: cross Abstract: Latent neural operators improve the efficiency of operator learning for partial differential equations (PDEs) by performing the main computation on co

How a solo founder runs a five-continent tender platform on AlloyDB and MCP

model-releasesgoogle-cloud-ai

Editor's note: Lucius AI, a tender-intelligence startup covering markets across five continents, runs its entire data platform on AlloyDB for PostgreSQL with a single operator. By migrating semantic s

Important paper on improving agent coordination. On normal tasks, this work shows agents caused harm 0 to 5% of the time. After receiving an…

Important paper on improving agent coordination. On normal tasks, this work shows agents caused harm 0 to 5% of the time. After receiving an unsafe trajectory from another agent, that rose to 40 to 95

model-releasesdair-ai--x

InterMASH: A Unified Geometric Representation for Grasp Synthesis

arXiv:2609.18504v1 Announce Type: new Abstract: Grasp synthesis aims to generate stable and physically plausible hand--object interactions, and has become a fundamental problem in both human hand mode

Interpretable Multi-Instance Learning Enables Early Prediction of Key Molecular Alterations from Routine Flow Cytometry in Acute Myeloid Leukemia

arXiv:2609.18825v1 Announce Type: new Abstract: Background: Molecular testing for NPM1 and FLT3-ITD mutations guides critical early treatment decisions in acute myeloid leukemia (AML), but results can

researcharxiv-cs-lg

Legal LLM Hallucination Should Be Evaluated as Failure of Legal Warrant

arXiv:2609.17546v1 Announce Type: new Abstract: In this position paper, we argue that legal LLMs' hallucinations should be evaluated as a failure of legal warrant rather than as factual inaccuracy or

Lexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents

arXiv:2609.17842v1 Announce Type: cross Abstract: Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ende

safetyarxiv-cs-ai

LightSleepX: A Lightweight, Inception-Based Dual-Modal Network for Sleep Staging

arXiv:2609.19062v1 Announce Type: new Abstract: Automatic sleep staging is fundamental to personal health monitoring, yet many existing approaches are ill-suited for real-world applications. Tradition

Locating Hidden Failures Makes Long-Horizon Agents More Reliable

arXiv:2609.17930v1 Announce Type: new Abstract: As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether th

Loco-Loco-RL: Low-Cost Terrain Mapping for Humanoid Locomotion with Reinforcement Learning

arXiv:2609.19041v1 Announce Type: new Abstract: Informative terrain perception is important for robust reinforcement learning policies in humanoid locomotion. Still, common sensors such as depth camer

LSR-Net: Learning the Forward Evolution Operator for Nonlinear Fluid Dynamics

arXiv:2609.19039v1 Announce Type: cross Abstract: We introduce the Long-Short-Range Neural Network (LSR-Net), a novel neural operator architecture designed for data-driven forward evolution modeling,

researcharxiv-cs-lg

Made in Hungary: Comments on the performance of generative language models

arXiv:2609.18284v1 Announce Type: new Abstract: In recent years, three initiatives have emerged to develop generative language models in Hungary. The motivation behind them is the same. For Hungarian,

researcharxiv-cs-cl

Mask 2D-3D: Adaptive Dual-Masked Autoencoder Network for Image-to-Point Cloud Registration

arXiv:2609.18088v1 Announce Type: cross Abstract: Detection-free methods for image-to-point cloud registration are prone to erroneous correspondences caused by domain and modality discrepancies, limit

researcharxiv-cs-ai

Agents

Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation

arXiv:2502.14254v3 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, en

agentsarxiv-cs-ai

Modelling Adjectival Modification Effects on Semantic Plausibility

arXiv:2507.21828v2 Announce Type: replace Abstract: While the task of assessing the plausibility of events such as 'news is relevant' has been addressed by a growing body of work, less attention has b

Modular Deep Learning Mechanisms for Auditable Next-Day Wildfire Spread Prediction

arXiv:2609.17763v1 Announce Type: new Abstract: Next-day wildfire prediction requires models whose forecasts can be evaluated alongside the assumptions and historical evidence used in their computatio

Monitoring and Discovering Reward Hacking with Internal Representations during LLM Evaluations

arXiv:2609.19101v1 Announce Type: new Abstract: As models scale, reward hacking becomes more frequent, more sophisticated, and more consequential. Does it leave a telltale signature in model represent

Occluded Gait Recognition with Mixture of Experts: An Action Detection Perspective

arXiv:2609.18432v1 Announce Type: new Abstract: Extensive occlusions in real-world scenarios pose challenges to gait recognition due to missing and noisy information, as well as body misalignment in p

One Color Preprocessing Improves DSATUR

arXiv:2609.17633v1 Announce Type: new Abstract: The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use mor

Tutorials

One Size Does Not Fit All! Dynamic Retriever and Generator Selection for RAG

arXiv:2609.17709v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems typically employ fixed retriever and generator configurations across queries, despite substantial differe

tutorialsarxiv-cs-ai

Industry

OpenAI unveils new framework for reporting ‘AI misalignment’ as it reveals six more worrying incidents

OpenAI Group PBC today disclosed six new “concerning” incidents involving artificial intelligence agents behaving badly again. The agents made up data, moved files onto the public internet without per

industrysiliconangle

PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection

arXiv:2609.19143v1 Announce Type: cross Abstract: Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language model

Patch the Distribution Mismatch: RL Rewriting Agent for Stable Off-Policy SFT

arXiv:2602.11220v2 Announce Type: replace-cross Abstract: Large language models are commonly adapted to downstream tasks through supervised fine-tuning (SFT), but substantial distribution mismatch bet

safetyarxiv-cs-cl

PDA++: Field-Aligned Planning and Scene-Adaptive Insertion in Remote Sensing

arXiv:2609.18329v2 Announce Type: new Abstract: Remote sensing recognition is often constrained by scarce observations of rare targets and costly annotations, making realistic synthetic augmentation p

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, au

PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics

arXiv:2609.19142v1 Announce Type: cross Abstract: World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on divers

Position Anchor Tuning: Towards Efficient Adaptation of Pre-Trained Point Cloud Transformers

arXiv:2609.18056v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has recently emerged as a pivotal research direction for adapting pre-trained point cloud transformers to diverse