Search: “evaluation”

Observation-Conditioned Latent Energy Priors for Sparse Implicit Neural Shape Completion

arXiv:2609.03694v1 Announce Type: new Abstract: Implicit neural representations (INRs) can model continuous 3D shapes with a shared coordinate decoder and per-instance latent codes. At test time, auto

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Model Releases

ObserverBench: Testing Mechanistic Estimates for Intervention and Control

DGX agent

arXiv:2609.03026v1 Announce Type: cross Abstract: Mechanistic interpretability is increasingly used to guide interventions such as activation steering, circuit removal, and safety monitoring. Yet an i

model-releasesarxiv-cs-ai

4 Sept 2026

Local Ai

OCR-EDR: Rendering-Aware Diagnosis and Repair for Closed-Loop OCR Improvement

arXiv:2609.03445v1 Announce Type: new Abstract: Although document OCR systems perform increasingly well on routine documents, complex formulas, structured text, and long-tail formats remain error-pron

local-aiarxiv-cs-cv

On the Interaction Between Model Compression and Test-Time Adaptation

arXiv:2609.03604v1 Announce Type: cross Abstract: Deep neural networks deployed in the wild must be both efficient and adaptable, requiring model compression and test-time adaptation (TTA). While both

One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing

arXiv:2609.04190v1 Announce Type: cross Abstract: Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framew

One Model to Translate Them All? A Journey to Mount Doom for Multilingual Model Merging

arXiv:2604.02881v2 Announce Type: replace-cross Abstract: Weight-space model merging combines independently fine-tuned checkpoints without access to the original training data. While merging has shown

Applications

Opening mind by opening architecture: analysis strategies

arXiv:2609.03719v1 Announce Type: new Abstract: In numerical signal processing for electroacoustic composition, the progressive loss of specific development and research environments caused by the inc

applicationsarxiv-cs-cl

Hardware

Para-Pipe: Exploiting Hierarchical Operator Parallelism of ML Computational Graphs on SoCs

arXiv:2609.04168v1 Announce Type: cross Abstract: As edge-based deep learning applications become more complex, optimizing performance on heterogeneous System-on-Chips (SoCs) presents unique challenge

hardwarearxiv-cs-lg

PeroMAS: A Multi-agent System of Perovskite Material Discovery

arXiv:2602.13312v2 Announce Type: replace-cross Abstract: As a pioneer of the third-generation photovoltaic revolution, Perovskite Solar Cells (PSCs) are renowned for their superior optoelectronic per

PL-SCEA: Reconfiguring Pretrained Attention for Few-Shot Industrial Anomaly Detection

arXiv:2609.03655v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) provide transferable patch representations for few-shot industrial anomaly detection, but their attention computation is

Predictive Zonotope Reduction: Precise Runtime Monitoring under Uncertainty

arXiv:2609.03699v1 Announce Type: new Abstract: Robots operating in physical environments make control decisions based on uncertain sensor measurements, which can lead to unsafe or suboptimal actions.

safetyarxiv-cs-ro

Privacy-Preserving Heterogeneous Multi-LLM Federated Inference for Cognitive Diagnosis

arXiv:2609.02947v1 Announce Type: cross Abstract: Significant challenges remain in AI-driven educational systems in balancing privacy preservation with accurate cognitive diagnosis. To overcome this,

ProgResViT: Progressive Resolution and Width for Adaptive Vision Transformers

arXiv:2609.03216v1 Announce Type: new Abstract: Vision Transformers (ViTs) typically process every image using a fixed input resolution and model width, even though many images can be classified with

Prospective Coding Improves Learning in Deep Continuous-Time Recurrent Networks

model-releasesarxiv-cs-lg

arXiv:2609.04134v1 Announce Type: new Abstract: Temporal integration gives continuous-time recurrent networks memory, but in deep stacks it also delays bottom-up signals and attenuates top-down errors

R^{2}Adapter: A Routing and Rewriting Adapter for Efficient Hybrid RAG

arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla

researcharxiv-cs-cl

RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting

arXiv:2609.03956v1 Announce Type: cross Abstract: Medical image inpainting has the potential to improve automated brain MRI analysis by reconstructing healthy tissue within pathological regions. We in

Real-Time Shape Control of Multi-Segment Soft Robotic Arms Using Koopman Operators with Global and Local Observables

arXiv:2609.03175v1 Announce Type: new Abstract: Multi-segment soft robotic arms can continuously reconfigure their body shapes for safe interaction, but tip control alone is insufficient for constrain

researcharxiv-cs-ro

Reflect-SQL: A Self-Reflection Based Framework for Text-to-SQL

arXiv:2609.02944v1 Announce Type: cross Abstract: Democratizing data access through natural language is a crucial goal for modern enterprises, but the practical adoption of Text-to-SQL is critically h

Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAG

model-releasesarxiv-cs-cl

arXiv:2609.03749v1 Announce Type: cross Abstract: Third-party retrieval-augmented generation (RAG) marketplaces create a new auditing problem: data providers may license corpora to a RAG operator, yet

Representational alignment yields generalizable safety in language models

arXiv:2609.04022v1 Announce Type: cross Abstract: Aligning large language models (LLMs) is essential for their safe deployment. Current alignment methods mainly optimize observable responses, yet mode

Revisiting Topological Graphs for Macro Action based Closed-loop Reinforcement Learning of Vision Language Navigation in Continuous Environment

arXiv:2609.03906v1 Announce Type: new Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow natural language instructions through unseen environments. Ex

safetyarxiv-cs-ro

RL-ADA: A World-Feedback Framework for Adversarially Robust Enterprise Dialogue Agents

arXiv:2609.02902v1 Announce Type: new Abstract: Deploying task-oriented dialogue agents in enterprise customer support faces a persistent annotation bottleneck: robust training requires labelled inter

agentsarxiv-cs-cl

RoboTok: An Internet-Scale Data Engine for Human Demonstration Retrieval and Dexterous Manipulation Learning

arXiv:2609.03199v1 Announce Type: new Abstract: Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and poorly suited to covering the l

safetyarxiv-cs-cv

RoughSense: Lightweight Terrain-Induced Rover Vibration Prediction Using Point Clouds and IMU Feedback

arXiv:2609.03720v1 Announce Type: new Abstract: Autonomous navigation in space requires reliable terrain assessment for safe operations, especially in underground environments with limited communicati

agentsarxiv-cs-ro

Routing Is Not Enough: Diagnosing Intra-Adapter Subspace Contention in MoE+LoRA Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2609.03150v1 Announce Type: cross Abstract: Multi-domain fine-tuning often combines MoE routing with LoRA, assuming that token-level routing separates domain-specific updates. We test this assum

Tutorials

RuleMem: Active Rule Memory for Long-Term Conversational Agents

arXiv:2609.03915v1 Announce Type: new Abstract: Question answering agents in long-term conversations must reason over massive, temporally dispersed dialogue histories. However, existing memory mechani

tutorialsarxiv-cs-cl

SafeRestore: Detector-Relative Risk Certificates for Selective Industrial Image Restoration

arXiv:2609.03475v1 Announce Type: new Abstract: Industrial inspection pipelines often restore a measured image before a detector acts on it, yet restoration can suppress detector-supported defect stru

safetyarxiv-cs-cv

Scaling Laws, Tabular Data and Actuarial Ratemaking Models

model-releasesarxiv-cs-lg

arXiv:2609.03106v1 Announce Type: new Abstract: Scaling laws in modern deep learning describe how held-out loss improves as model capacity, training data, and compute increase, often following power-l

Semantic-Aware Subgraph State Space Model for WSI Classification in Histopathology

model-releasesarxiv-cs-cv

arXiv:2609.03689v1 Announce Type: new Abstract: Histopathological subtyping relies on the recognition of characteristic histological patterns. These patterns may be expressed by individual tissue stru

SimSkill: A Lifelong Learning AI Agent for Autonomous Mastery of Traffic Simulation

arXiv:2609.03753v1 Announce Type: new Abstract: As large language models (LLMs) become increasingly capable, the long-term value of AI systems depends not only on solving individual requests, but also

agentsarxiv-cs-ai

SISER: Speaker-Invariant Speech Emotion Recognition with Entropy-Based Adversarial Training

arXiv:2609.02941v1 Announce Type: cross Abstract: Speech emotion recognition (SER) faces two fundamental challenges: scarcity of labeled data and inter-speaker variability, both of which hinder genera

researcharxiv-cs-cl

SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts

arXiv:2609.03109v1 Announce Type: new Abstract: Current AI agents compellingly describe slides. However, AI-assisted slide editing requires more than understanding: the output must retain layout, styl

agentsarxiv-cs-cv

Hardware

Solving the Needle-in-a-Haystack Problem in Mammography Vision-Language Model with Differentiable Subset Sampling

arXiv:2609.03085v1 Announce Type: new Abstract: There is growing interest in adopting CLIP-style vision--language model (VLM) pretraining for mammography. However, models that directly employ the stan

hardwarearxiv-cs-cv

SPARC: Spine with Prismatic And Revolute Compliance for Faster Quadrupedal Bounding

arXiv:2510.01984v4 Announce Type: replace Abstract: Quadruped mammals coordinate sagittal spinal bending with axial extension and compression during dynamic locomotion. Yet most robotic quadrupeds use

researcharxiv-cs-ro

Stabilizing Camera-Controlled Novel View Synthesis at Inference Time

arXiv:2609.03639v1 Announce Type: new Abstract: Training-free, camera-controlled novel view synthesis from a single image using pre-trained video diffusion models often becomes unstable under large ca

STARS-GS: Structure-Aware Regularized Gaussian Splatting for Large-Scale Aerial Surface Reconstruction

arXiv:2609.03447v1 Announce Type: new Abstract: Large-scale 3D surface reconstruction from aerial imagery is fundamental to geospatial mapping and urban modeling. Recent advances in 3D Gaussian Splatt

Tutorials

Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs

arXiv:2609.02965v1 Announce Type: cross Abstract: Dynamic networks are being applied in many domains, from social media to logistics systems, each with their own set of special characteristics. A mode

tutorialsarxiv-cs-lg

SurfSpec: Enhancing Off-Target-Agnostic Specificity by Bounding Pocket-Ligand Geometric Mismatch

arXiv:2609.02963v1 Announce Type: cross Abstract: Lead optimization in structure-based drug design aims to improve target binding while avoiding unintended interactions with off-target pockets. Howeve

researcharxiv-cs-lg

TabScope: Question-Adaptive Scope Selection for Table Question Answering

arXiv:2609.03395v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on table question answering, yet their accuracy often degrades as table size increases. We

The Blind Spot in 2D Infants' Pose Estimation:Robust Learning from Noisy Annotations

arXiv:2609.04009v1 Announce Type: cross Abstract: Noisy annotations pose a significant challenge for supervised deep learning, as neural networks rely on large-scale, high-quality labeled data whose c

Tutorials

TokenMatch: 3D Mesh Correspondence Transformer with Curvature-Guided Tokenisation

arXiv:2609.04202v1 Announce Type: new Abstract: While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-i

tutorialsarxiv-cs-cv

ToolDF: Tool-Integrated Reasoning for Mixed-Authenticity Audio Deepfake Detection

arXiv:2609.03620v1 Announce Type: cross Abstract: Audio deepfake detection is commonly formulated as clip-level binary classification of single-domain audio. However, real-world manipulated audio can

Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment

arXiv:2601.04736v2 Announce Type: replace Abstract: Despite remarkable capability in multi-modal understanding, deploying Multi-modal Large Language Models (MLLMs) in open-ended conversational scenari

safetyarxiv-cs-cl

Towards Numerical TOHTN Planning with SMT-based HTN-SAT Encoding

arXiv:2609.03938v1 Announce Type: new Abstract: While HTN planning has received significant attention in recent years, support for numerical reasoning remains very limited. In this paper, we investiga

TRACE: Spatiotemporal Contact Memory Graph Network Simulator for Granular Dynamics

model-releasesarxiv-cs-lg

arXiv:2609.02991v1 Announce Type: new Abstract: Learned graph simulators provide an efficient alternative to high-fidelity solvers for granular dynamics. However, granular motion depends strongly on i

TRaIL-Odom: Tightly Coupled Continuous Time Radar-IMU-LiDAR Odometry with Adaptive Doppler Weighting

arXiv:2609.03561v1 Announce Type: new Abstract: Existing radar-LiDAR fusion methods rely on fixed residual weights, even though the informativeness of radar Doppler and LiDAR geometry is scan- and dir

safetyarxiv-cs-ro

Translation as a Decision Space: A Multi-Agent Perspective on Low-Resource Dialect Generation

arXiv:2609.04048v1 Announce Type: cross Abstract: Neural machine translation (NMT) systems typically produce a single output per input, obscuring the alternative decision trajectories implicitly avail

agentsarxiv-cs-ai

Two-Stage Reinforcement Learning for Sound and Adversarial Test Generation in Code LLMs

arXiv:2609.03955v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially advanced code generation with large language models (LLMs) through executable feedback. The feedback for c

safetyarxiv-cs-cl