Search: “evaluation”

MinkowskiPE: Minkowski Positional Encoding for Spatiotemporal Perception

arXiv:2609.33804v1 Announce Type: cross Abstract: Modeling spatiotemporal coupling is a key challenge in building physical intelligence across scales, from microscopic to macroscopic. Existing models

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Research

Modernising the Compressed-Domain Video Captioner: A Controlled Study of SigLIP2 and GPT-2 Substitutions

DGX agent

arXiv:2609.31700v1 Announce Type: new Abstract: Compressed-domain video captioning avoids full video decoding by operating directly on I-frames, motion vectors and residuals, trading a small amount of

researcharxiv-cs-cv

29 Sept 2026

Multimodal LLMs Outperform Pathology Foundation Models in Cross-Domain Histological Similarity

arXiv:2609.32876v1 Announce Type: new Abstract: State-of-the-art pathology foundation models, trained on millions of histology tiles, can fail to preserve tissue similarity when comparisons cross slid

Natural Image Autoencoder-Based fMRI Representations for Trait and State Prediction

arXiv:2609.34167v1 Announce Type: new Abstract: Foundation models pre-trained on large-scale fMRI datasets have shown strong downstream performance, but at substantial data and computation cost. To in

local-aiarxiv-cs-cv

Natural State-Prediction Accuracy can Hide Weak Controlled Responsiveness in VLA Readouts

arXiv:2609.34684v1 Announce Type: cross Abstract: Accurately decoding object states from the internal representations of vision-language-action (VLA) models does not establish that the predictions res

safetyarxiv-cs-cv

NetInjectBench: Benchmarking Indirect Prompt Injection in Tool-Using Large Language Model Agents for Network Operations

arXiv:2607.10490v2 Announce Type: replace-cross Abstract: Tool-using large language model (LLM) agents are attractive for network operations, but tickets, alerts, logs, runbooks, and ChatOps messages

Octree-based Video Representation

arXiv:2609.33100v1 Announce Type: new Abstract: Video models commonly use uniform grids even though visual complexity varies substantially across space and time. We introduce OctVideo, which approxima

local-aiarxiv-cs-cv

OmniFysics-Captioner Technical Report: Grounding Omni-Modal Understanding in the Physical World for Better Captioning

arXiv:2609.31714v1 Announce Type: new Abstract: Building omni-modal models with physical intelligence requires fine-grained supervision that captures physical evidence such as contact, support, deform

PalmLeaf-VQA: A Multi-Script Visual Question Answering Benchmark for Historical Palm-Leaf Manuscript Understanding Across Diverse Regions

arXiv:2609.31651v1 Announce Type: new Abstract: Historical manuscripts remain largely absent from modern vision-language benchmarks, leaving open how well multimodal large language models (MLLMs) hand

PanoFuse: Panorama-Enhanced Vision-Language-Action Learning with Decoupled Semantic-Geometric Routing

arXiv:2609.31717v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies have shown promising performance in language-conditioned robotic manipulation. However, most existing VLA systems

PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory

arXiv:2609.31716v1 Announce Type: new Abstract: Persistent semantic occupancy mapping is essential for embodied scene understanding. However, perspective-based systems provide limited spatial coverage

applicationsarxiv-cs-cv

Perceptual Quality Loss or Loss of Perceptual Quality?

arXiv:2609.35054v1 Announce Type: cross Abstract: Contemporary deep speech enhancement (SE) models are often trained with specific auxiliary terms in the loss function as a way to improve their perfor

PHIRL: Aligning Learned Rewards with Task Progress for Inverse Reinforcement Learning

arXiv:2609.31855v1 Announce Type: new Abstract: Human demonstrations provide dense policy-level information but sometimes lack local precision. Human feedback presents accurate local critiques, but of

local-aiarxiv-cs-ro

PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks

arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha

safetyarxiv-cs-lg

PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents

arXiv:2609.32801v1 Announce Type: cross Abstract: Embodied task planners may produce multi-step plans whose subtask dependencies and interactions with the environment create physical risks during exec

PolyStepOR: Learning to Decide Without Optimal Decisions

arXiv:2609.32465v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictors for downstream decision quality, but often relies on optimal reference decisions that are expensive to

applicationsarxiv-cs-lg

PolyTopoBench: A Benchmark for Complex Vector Polygon Generation from Remote Sensing Imagery

arXiv:2609.32856v1 Announce Type: new Abstract: Vector polygon generation converts visual inputs, e.g., remote sensing (RS) images, into vectorized polygonal geometries, supporting applications such a

Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

arXiv:2609.33928v1 Announce Type: new Abstract: Predicting spatial gene expression from histology images could scale spatial transcriptomics (ST) to image-only cohorts, but conventional histology-base

Prosodic ABX: A Language-Agnostic Method for Measuring Prosodic Contrast in Speech Representations

arXiv:2604.02102v2 Announce Type: replace-cross Abstract: Speech representations from self-supervised speech models (S3Ms) are known to be sensitive to phonemic contrasts, but their sensitivity to pro

Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them

arXiv:2609.35023v1 Announce Type: new Abstract: Lightweight scene proxies let creators control scene layout and motion while leaving room for imagination in appearance, lighting, and visual effects. H

QuantForge: Discovering Residual Decompositions for MXFP4 Post-Training Quantization

arXiv:2609.34680v1 Announce Type: new Abstract: Four-bit post-training quantization can reduce the memory demands of large language models, but preserving accuracy under strict MXFP4 W4A4 requires coo

applicationsarxiv-cs-lg

RAEGL: Risk-Aware Evidence-Gated Learning for Selective Contextual Routing under Temporal Shift

arXiv:2609.33340v1 Announce Type: new Abstract: Contextual specialization can improve forecasting accuracy, but a correction selected on one historical interval may become unreliable under temporal di

applicationsarxiv-cs-lg

REALM: A Coarse-to-Fine Generative Framework for Embodied Reactive Listening

arXiv:2609.33095v1 Announce Type: new Abstract: Generating responsive listener facial motion is an important task for embodied conversational AI. Two modeling challenges are central: accounting for th

local-aiarxiv-cs-ro

ReGDiff: Guided Diffusion in Regulated Latent Space for Exploring Metamaterial Voxel Geometry

arXiv:2609.34231v1 Announce Type: new Abstract: Metamaterials are artificially engineered structures whose mechanical and physical behaviors are strongly shaped by geometry rather than composition. Vo

REMEDY: How Far Is Video Generation from Medical Education World Models?

arXiv:2609.32460v1 Announce Type: new Abstract: Recent video generation models produce realistic videos and show potential as a foundation for world models. These advances create opportunities for gen

Agents

ReplayLens: Auditing Agents' Use of Outcomes

arXiv:2609.34177v1 Announce Type: cross Abstract: When an agent reuses logged experience, a changed decision may reflect the recorded score, the action's name, or the record's position in storage. Sta

agentsarxiv-cs-lg

ResonAct: Streaming Metrics for Runtime Diagnosis and Self-Healing in Multi-Agent Systems

arXiv:2609.34701v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple specialized agents, external tools, and long-runni

local-aiarxiv-cs-lg

Rethinking Training-Inference Mismatch in LLM Reinforcement Learning: Where It Arises and How to Correct It

arXiv:2609.32444v1 Announce Type: new Abstract: We study training-inference mismatch in reinforcement learning with verifiable rewards (RLVR) for large language models, where rollouts are sampled by a

ReVA: A Scene-Centric Dataset Beyond Repetition for Remote Sensing Video Question Answering

arXiv:2609.35507v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable advances in remote sensing. However, existing remote sensing multimodal reasoning

RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers

model-releasesarxiv-cs-ro

arXiv:2609.34210v1 Announce Type: new Abstract: Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchma

Agents

Robot Tool Design from Scratch via Behavior-Aware Hierarchical Optimization

arXiv:2609.35479v1 Announce Type: new Abstract: The ability to design a tool for a task marks a level of intelligence beyond merely understanding, selecting, or using one. Existing methods for robotic

agentsarxiv-cs-ro

Robust and Efficient MuJoCo-based Model Predictive Control via Web of Affine Spaces Derivatives

arXiv:2512.21109v4 Announce Type: replace Abstract: MuJoCo is a powerful and efficient physics simulator widely used in robotics. One common way it is applied in practice is through Model Predictive C

researcharxiv-cs-ro

RoPE is Dead, Long Live RoPE: Towards Scalable Data-aware Positional Encodings

arXiv:2609.34556v1 Announce Type: cross Abstract: Transformers process tokens without any inherent notion of order, making positional encoding a fundamental requirement rather than an architectural re

safetyarxiv-cs-lg

Same Probe, Different Numbers: Are Activation Probes Robust to Inference-Time Numerical Non-Determinism?

arXiv:2609.31796v1 Announce Type: new Abstract: Activation probes are increasingly used to monitor LLMs in deployment. A probe is typically trained under one inference configuration, then used under w

Self-Evolving Time-Series Forecasting Agents with Episodic Memory and Online Policy Learning

arXiv:2609.32689v1 Announce Type: new Abstract: LLM-based agents are increasingly used for time-series forecasting because they can organise contextual information, perform multi-step analysis, and gu

Separating personal from population gains when calibrating EEG foundation models for new users

arXiv:2609.34801v1 Announce Type: new Abstract: Foundation models are increasingly adapted to individual users, but an apparent personalization gain can simply reflect a stronger population model. Thi

Server-Enforced Watermarking in U-Shaped Split Federated Learning

arXiv:2511.14422v2 Announce Type: replace-cross Abstract: U-shaped split federated learning (U-SFL) enables resource-constrained Internet of Things devices to collaboratively train models with an edge

local-aiarxiv-cs-lg

Simple Diffusion Language Models Are More Effective Few-Step Generators Than Reported

arXiv:2609.33947v1 Announce Type: cross Abstract: Diffusion language models (DLMs) promise fast parallel generation, yet high-quality samples often require large number of refinement steps, which dimi

SNaP: One-Step Posterior Sampling for Noisy Inverse Problems

arXiv:2609.34071v1 Announce Type: new Abstract: Diffusion and flow-matching models can produce high-quality posterior samples for inverse problems, but typically require tens to thousands of network e

Source Anchoring for Physical Consistency in Flow Matching Models

arXiv:2609.33510v1 Announce Type: new Abstract: Deep generative models are used to solve partial differential equations and model distributions of physical system states, but ensuring that the generat

STeP: Signal Temporal Logic for Precise Specifications for Action Generation with Vision Language Models

model-releasesarxiv-cs-ro

arXiv:2607.18580v2 Announce Type: replace Abstract: Natural-language robot instructions often specify more than a coarse task goal: they may impose spatial, temporal, and logical requirements that mus

Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models

arXiv:2609.35002v1 Announce Type: new Abstract: Visual token compression reduces the inference cost of Large Vision-Language Models (LVLMs). However, aggregate robustness measures do not reveal whethe

SyncRA: Learning Temporal Correspondence in Omni-Modal Models

arXiv:2609.34363v1 Announce Type: new Abstract: Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at th

Hardware

Systematic Exploration of Multi-core Architectures for Efficient LLM Serving using WaferAI-SIM

arXiv:2510.05632v2 Announce Type: replace-cross Abstract: With the widespread adoption of Large Language Models (LLMs), the demand for high-performance LLM inference services continues to grow. Multi-

hardwarearxiv-cs-lg

Teach to Learn: Hint Annealing for Self-improving LLM Reasoning

arXiv:2609.34975v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) improves language-model reasoning by comparing verified rewards among multiple solution rollouts for each quer

Temporal Heterogeneous Graph Pretraining for Relational Deep Learning

arXiv:2609.35219v1 Announce Type: new Abstract: Relational deep learning models database rows and foreign-key links as a heterogeneous graph for prediction from record attributes and relational contex

The Platonic Universe: Do Foundation Models See the Same Sky?

arXiv:2509.19453v2 Announce Type: replace-cross Abstract: We investigate when foundation models converge towards shared representations, and how this convergence depends on model capacity, training re

safetyarxiv-cs-lg

Timed Rule-Based Supervision of an End-to-End Autonomous Parking Policy

arXiv:2609.31773v1 Announce Type: new Abstract: We study whether a manually specified runtime supervisor can correct recurring failures of an existing end-to-end parking policy in a fixed CARLA parkin

safetyarxiv-cs-ro