Search: “evaluation”

arXiv:2609.15895v1 Announce Type: new Abstract: Physical AI relies on frequently-updated, latency-sensitive video stream to perceive, reason, and interact with the physical world, resulting in strict

hardwarearxiv-cs-ro

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Model Releases

GorillaWatch: An Automated System for In-the-Wild Gorilla Re-Identification and Population Monitoring

DGX agent

arXiv:2512.07776v2 Announce Type: replace Abstract: Monitoring critically endangered western lowland gorillas is currently hampered by the immense manual effort required to re-identify individuals fro

model-releasesarxiv-cs-cv

15 Sept 2026

GP-VMimesSMA: Benchmarking General-Purpose Vision Models and Specialized Architectures for 2D Medical Image Segmentation

arXiv:2603.13044v2 Announce Type: replace-cross Abstract: Medical image segmentation (MIS) is a fundamental component of computer-assisted diagnosis and clinical decision support. Over the past decade

researcharxiv-cs-ai

GROOVE: Geometry-Guided Reduction of Operational-Space Jerk in VLA Execution

model-releasesarxiv-cs-ro

arXiv:2609.13695v1 Announce Type: new Abstract: Chunked vision language action (VLA) policies execute several commands per query, but jerk within chunks and across replanning boundaries can induce osc

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

model-releasesarxiv-cs-lg

arXiv:2609.13285v1 Announce Type: cross Abstract: The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with sequence length. Grouped-query at

GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space

arXiv:2603.19308v2 Announce Type: replace-cross Abstract: In autonomous driving, multi-agent collaborative perception enhances sensing capabilities by enabling agents to share perceptual data. A key c

HarnessBandit: Joint Learnability-Transferability Scheduling for Multi-Harness Agentic Reinforcement Learning

arXiv:2609.13739v1 Announce Type: cross Abstract: Language-model agents are increasingly deployed through diverse harnesses that differ in system prompts, tool schemas, control loops, and trajectory f

Harnessing human expertise for high-precision robotic assembly in industrialized construction: A sample-efficient installer-in-the-loop interactive reinforcement learning framework

arXiv:2609.13234v1 Announce Type: new Abstract: Industrialized construction imposes stringent precision requirements on robotic assembly of modular components such as prefabricated window units. In to

safetyarxiv-cs-ro

Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures

arXiv:2607.27617v2 Announce Type: replace Abstract: Identical language-model answers can arise from hidden states that support different future computations, so current-answer probes do not establish

Local Ai

HiGFRL: Hierarchical Graph Fusion-Driven Reinforcement Learning for Dependency-Aware Task Scheduling in Heterogeneous Cloud

arXiv:2609.14968v1 Announce Type: new Abstract: Online scheduling of dependency-aware tasks in heterogeneous cloud clusters is a fundamental yet challenging problem due to the complex interplay betwee

local-aiarxiv-cs-lg

HISPO: Hierarchical Importance-Sampling Policy Optimization with Entropy-Derived Segments

arXiv:2609.15471v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a central approach for improving mathematical reasoning in language models, but long-fo

How User-AI Mistreatment Occurs and Matters in Conversational Systems?

arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding

Local Ai

Human Pose-Constrained UV Map Estimation

arXiv:2501.08815v2 Announce Type: replace Abstract: UV map estimation is used in computer vision for detailed analysis of human posture or activity. Previous methods assign pixels to body model vertic

local-aiarxiv-cs-cv

HyperProve: Answer-Guided Hypergraph Expansion for Multi-Hop Question Answering

arXiv:2609.13768v1 Announce Type: new Abstract: Multi-hop question answering often fails when retrieval treats evidence as isolated matches to the original question, since the facts needed to answer a

Agents

HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

arXiv:2609.15938v1 Announce Type: new Abstract: Scientific agents contribute to hypothesis discovery by synthesizing evidence, assessing proposals, and developing new explanations. Recent systems comb

agentsarxiv-cs-cl

Inoculation Midtraining with Learned Neologisms

arXiv:2609.15886v1 Announce Type: new Abstract: Large language models (LLMs) often learn both desirable and undesirable properties during post-training. We study whether midtraining, an earlier traini

Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows

arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi

researcharxiv-cs-cv

Interpretable Temporal Video Reasoning with EventGraph and EventField

arXiv:2609.13258v1 Announce Type: cross Abstract: We present a structured temporal video reasoning pipeline built around a discrete EventGraph, a continuous EventField, and a human-readable EventGlyph

Interpreting hierarchical organisation of speaker embeddings

arXiv:2609.15203v1 Announce Type: cross Abstract: Speaker recognition neural networks learn latent representations (i.e. speaker embeddings) from input utterances to recognise speaker identities. Howe

tutorialsarxiv-cs-ai

Hardware

Is Semantic SLAM Ready for Embedded Systems ? A Comparative Survey

arXiv:2505.12384v2 Announce Type: replace Abstract: Semantic SLAM holds promise for robust robot navigation in complex environments, but its practicality on embedded systems remains uncertain. This pa

hardwarearxiv-cs-ro

JEPLO: Joint-Embedding Predictive Learning for LiDAR-Based Legged Locomotion

arXiv:2609.15770v1 Announce Type: new Abstract: Light detection and ranging (LiDAR) remains less explored than RGB-D sensing for perceptive legged locomotion, and existing LiDAR-based approaches often

safetyarxiv-cs-ro

Know When to Stop, Where to Restart: Accelerating Multi-Turn Agentic On-Policy Distillation

arXiv:2609.14636v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a standard approach for transferring capabilities from large teachers to compact students. Its cost, however,

Knowledge-Enriched Structured EHR Features for 30-Day Hospital Readmission Prediction on MIMIC-IV

arXiv:2609.15713v1 Announce Type: new Abstract: Recent approaches to 30-day hospital readmission prediction rely on pre-trained language models applied to discharge summaries. Although these methods a

Language-Guided Representation Learning for Robust Cross-Sensor Material Recognition

arXiv:2609.14783v1 Announce Type: cross Abstract: Robots need touch to manipulate objects safely and reliably, as many properties, such as softness, texture, and contact stability, are hard to infer f

Agents

Large-FOV RGBD Imaging via Structured PSF Coding in a Bio-inspired Monocentric System

arXiv:2510.25314v2 Announce Type: replace Abstract: High-fidelity large-field-of-view (LFOV) 3D sensing, essential for autonomous platforms, is hindered by the coupling of anisotropic off-axis aberrat

agentsarxiv-cs-cv

LayerRoute: Adaptive Layer-Skipping with LoRA-Preserved Quality for Efficient LLM Inference

arXiv:2609.13682v1 Announce Type: cross Abstract: We introduce LayerRoute, a parameter-efficient method for adaptive transformer layer-skipping that combines per-layer hard-gated routing (trained via

Learning Manipulation-Sufficient Representations via Outcome Bottlenecks

arXiv:2609.13235v1 Announce Type: cross Abstract: Networked manipulation endpoints couple perception to actuation across compute- and bandwidth-limited links, yet commonly exchange dense geometric sta

safetyarxiv-cs-cv

Learning Metastable Dynamics

arXiv:2609.14712v1 Announce Type: cross Abstract: Metastability---a phenomenon where systems remain trapped in quasi-stable states before abruptly transitioning under rare perturbations---is ubiquitou

tutorialsarxiv-cs-lg

Learning Multi-Agent Task Assignment and Navigation in the Factory: from Simulation to Real Robots

arXiv:2609.14567v1 Announce Type: cross Abstract: Reinforcement learning (RL) has shown considerable promise for robotic decision-making, yet deploying multi-agent RL (MARL) on physical multi-robot sy

safetyarxiv-cs-lg

Learning Through Energy Refinement and Manifold Projection: A Cooperative EBM-AE Framework

arXiv:2609.13917v1 Announce Type: new Abstract: Energy-Based Models (EBMs) provide a flexible framework for generative modeling by learning an energy landscape that assigns low energy values to realis

Learning to Refer from Estimated Listener Gaze

arXiv:2609.14207v1 Announce Type: new Abstract: We propose to finetune vision-language models to generate more pragmatically optimal referring expressions by transforming observations of incremental l

LePlanner: An Iterative Amortized Controller For World Models

arXiv:2609.13845v1 Announce Type: cross Abstract: World models trained with joint-embedding predictive architectures learn compact, structured latent representations from physical interaction, yet pla

Lexical Prompt Compression for Large Language Models: A Training-Free, Deterministic Pipeline with Empirical Pareto Analysis Across Eleven Task Categories

arXiv:2609.13154v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have made prompts increasingly large and complex. Techniques such as chain-of-thought reasoning (Wei et

LLM Probability Concentration: How Alignment Shrinks the Generative Horizon

arXiv:2506.17871v4 Announce Type: replace-cross Abstract: Despite their impressive capabilities, aligned large language models (LLMs) often generate outputs that lack diversity. What drives this consi

Look Before You Leap: Factual Decoding with Internal Attribution Signals

arXiv:2609.15745v1 Announce Type: cross Abstract: Hallucination remains a critical challenge in large language models (LLMs), where early factual errors compound through autoregressive generation in a

researcharxiv-cs-ai

Applications

Low Clearance Hinge Joint Mechanism Based on 3D Printing on Sheet Fabrication Methodology

arXiv:2609.15276v1 Announce Type: new Abstract: This paper presents a low-clearance hinge joint mechanism based on the 3D printing on sheet fabrication method. This approach simplifies the fabrication

applicationsarxiv-cs-ro

Hardware

LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows

arXiv:2609.15863v1 Announce Type: new Abstract: Video diffusion models are stochastic and hard to control: precise content often requires repeated sampling without guaranteed success, and long-horizon

hardwarearxiv-cs-cv

Machine Learning under Imperfect Data: Challenges and Methods

model-releasesarxiv-cs-lg

arXiv:2609.13914v1 Announce Type: new Abstract: Machine-learning models are commonly developed under an assumption that training and test data are sufficiently complete, balanced, labelled, and drawn

Machine Unlearning for Speech Question Answering in Large Audio-Language Models

arXiv:2609.13195v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently shown strong capabilities in speech understanding and question answering (QA), but they also inherit

MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training

arXiv:2609.15221v1 Announce Type: cross Abstract: Passive acoustic monitoring can measure biodiversity at larger scales, but time--frequency annotation of animal vocalizations is expensive, site-speci

Math for AI safety: an invitation for mathematicians

arXiv:2609.15289v1 Announce Type: cross Abstract: Artificial intelligence threatens to outrun human understanding and control. New mathematics is needed to design AI that is legible, steerable, and co

MessyMem: Learning-from-Doing Memory for Mobile Manipulation

arXiv:2609.15976v1 Announce Type: new Abstract: Mobile manipulators deployed across many rooms and visits should improve with experience: after discovering that a cabinet is locked or finding an objec

tutorialsarxiv-cs-ro

Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States

arXiv:2609.15972v1 Announce Type: new Abstract: As language models become more capable, long-term collaboration in learning, reasoning, and decision-making calls for a deeper understanding of the peop

MoARa: Module-Aware Rank Allocation and Structure-Preserving Decomposition for Low-Rank LLM Pre-training

arXiv:2609.15037v1 Announce Type: cross Abstract: Low-rank gradient projection reduces the optimizer-state memory cost of large language model (LLM) pretraining, but the steps and wall-clock time need

Applications

MoVT: Video-Augmented Motion Tokenizer for Text-to-Motion Generation

arXiv:2609.14965v1 Announce Type: new Abstract: Text-driven 3D human motion generation models face significant challenges in responding to diverse and unconstrained textual prompts, primarily due to t

applicationsarxiv-cs-cv

Multi-Domain Motion Embedding: Expressive Real-Time Mimicry for Legged Robots

arXiv:2512.07673v2 Announce Type: replace Abstract: Effective motion representation is crucial for enabling robots to imitate expressive behaviors in real time, yet existing motion controllers often i

researcharxiv-cs-ro

Multi-source Transfer Learning of Time Series with a Shapelet-based Distance Measure

arXiv:2609.15148v1 Announce Type: new Abstract: Transfer learning is an effective technique for addressing data scarcity in deep learning for time series classification, but its success depends on the

Multi-View Molecular Representation Learning with Hierarchical Graphs and Contextualized Fingerprints

arXiv:2609.15611v1 Announce Type: cross Abstract: Molecular property prediction requires representations that generalize from limited labeled data to structurally novel compounds. Existing molecular p

tutorialsarxiv-cs-ai