Search: “evaluation”

CipherGenome: Homomorphic Inference for Genomic Mixture-of-Experts

model-releasesarxiv-cs-lg

arXiv:2609.35883v1 Announce Type: cross Abstract: Genome foundation models are growing into sparse mixture-of-experts (MoE) networks whose expert weights no longer fit on the machines that hold the se

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Agents

Co-Linguistics: AI-augmented Theory Construction in Linguistics

DGX agent

arXiv:2609.37635v1 Announce Type: new Abstract: LLMs have been studied in recent linguistics as potential models of humans' linguistic abilities. Here we discuss an entirely different use of AI, namel

agentsarxiv-cs-cl

30 Sept 2026

Code4Scene: Benchmarking Coding Agents for Constructing and Editing 3D Scenes

arXiv:2609.36777v1 Announce Type: new Abstract: Frontier coding agents can now write and execute code that authors 3D environments, but whether they reliably understand 3D structure and precisely cont

CoMemBench: Benchmarking Collaborative Memory Boundaries across Multi-Agent Workflow Topologies

arXiv:2609.32192v2 Announce Type: replace Abstract: Multi-agent workflows require task-relevant information to be shared across agents, while irrelevant, stale, unverified, or incompatible information

Compress to Remember: Learning Compact Memory via On-Policy Distillation for Long Video Generation

arXiv:2609.36364v1 Announce Type: cross Abstract: Standard video generators do not natively compact historical context into reusable memory tokens. As generation continues, the growing history makes i

safetyarxiv-cs-ai

CoSec: Benchmarking Agent Security in Communities

arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community bound

Demistifying Data and Simulator Assumptions in Supervised Causal Discovery

arXiv:2609.37446v1 Announce Type: new Abstract: Supervised causal discovery learns to infer causal structure for a new dataset from training datasets paired with structural labels. These training pair

Diagnosing and Improving Probabilistic Reasoning in Large Language Models

arXiv:2609.38005v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as decision assistants who must reason probabilistically from available evidence under explicit d

DimGrow: Memory-Efficient Field-level Embedding Dimension Search

arXiv:2505.12683v2 Announce Type: replace Abstract: Key feature fields need bigger embedding dimensionality, others need smaller. This demands automated dimension allocation. Existing approaches, such

Disentangling Spurious Correlations in Vision-Language-Action Models via Predicting Domain-Invariant Latent Lookahead

arXiv:2609.37165v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models remain brittle under visual distribution shifts, often relying on spurious correlations tied to domain-specific fact

safetyarxiv-cs-ro

Agents

doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving

arXiv:2609.38028v1 Announce Type: cross Abstract: Autonomous vehicles interacting with passengers through natural language must reason beyond immediate commands. Passenger intent may span multiple sta

agentsarxiv-cs-ai

DualTrack: Synchronized speech-gesture generation via symmetric coupling of pretrained priors

arXiv:2609.36624v1 Announce Type: new Abstract: Joint speech-gesture synthesis must coordinate two modalities despite limited paired data. Existing approaches often lack bidirectional interaction, hav

Efficient Offline Learning of Ranking Policies via Top-k Policy Decomposition

arXiv:2609.36740v1 Announce Type: new Abstract: Many recommender systems such as for e-commerce and news platforms aim to provide users with rankings they are likely to interact with. Off-Policy Learn

safetyarxiv-cs-lg

Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs

arXiv:2609.36157v1 Announce Type: cross Abstract: Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task. This

Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents

arXiv:2609.36365v1 Announce Type: new Abstract: Can interaction formats and textual scaffolds help large language model (LLM) agents make better decisions, and do better decisions come with better exp

EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

arXiv:2609.37686v1 Announce Type: new Abstract: Autonomous agents have made rapid progress in general-purpose computer use, but reliable automation of professional industrial engineering remains out o

EnterpriseBench: Benchmarking LLM Agents on Enterprise-Level Strategic Reasoning and Decision-Making

arXiv:2609.37658v1 Announce Type: new Abstract: LLM agents are increasingly expected to support enterprise workflows, where tasks often involve missing information, uncertainty, feedback, and long-ter

Executor-aware Candidate Selection via a Feasibility Certificate

arXiv:2609.36597v1 Announce Type: new Abstract: Modular robotic systems often separate motion planning from a downstream executor that enforces state-dependent hard constraints. A candidate that is ge

researcharxiv-cs-ro

Exploring In-Context Learning for Handwritten Text Recognition

model-releasesarxiv-cs-cv

arXiv:2609.37195v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) systems have become an indispensable tool for the digitization of historical documents. Not only do they cut down tim

Foundation-Model-Guided Topology-Aware Semantic Risk Fields for Manipulation

arXiv:2609.36640v1 Announce Type: new Abstract: Robot motion planning in everyday environments must satisfy hard geometric constraints while accounting for context-dependent semantic risk. We present

safetyarxiv-cs-ro

From Neurons to Conversation: Speech Brain-Computer Interfaces

arXiv:2609.36736v1 Announce Type: cross Abstract: Speech brain-computer interfaces (BCIs) aim to restore communication by transforming neural activity related to speech, language, or communicative int

researcharxiv-cs-cl

From Retrieval to Reasoning: Agentic Mechanism Prediction from Cell Painting Profiles

arXiv:2609.36406v1 Announce Type: new Abstract: Cell Painting is a high-content morphological profiling assay widely used for phenotype-based biological inference, with mechanism of action (MOA) predi

GeoOutageBench: Benchmarking Ambiguity-aware, Ontology-grounded Geospatiotemporal KGQA for Multimodal Power Outage and Resilience Analysis

arXiv:2609.36082v1 Announce Type: new Abstract: We introduce GeoOutageBench, a benchmark for assessing LLM-based geospatiotemporal KGQA for multimodal outage and resilience analysis. Unlike existing K

GeoWind2Plan: Mission-Time 3D Urban Wind Prediction for Energy-Efficient UAV Planning

arXiv:2609.36056v1 Announce Type: new Abstract: In urban low-altitude flight, buildings reshape ambient wind into spatially varying 3D flow, making unmanned aerial vehicle (UAV) energy depend on local

local-aiarxiv-cs-ai

Grab a Coffee: Future-Aware Guidance for Discrete Diffusion with Compiled Objectives

arXiv:2609.35924v1 Announce Type: new Abstract: Discrete diffusion models generate sequences by iteratively resolving multiple tokens in parallel, offering a flexible alternative to left-to-right gene

HACo: Learning Haptic Active Compliance for Force-Aware Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.36596v1 Announce Type: new Abstract: Contact-rich dexterous manipulation requires policies that translate physical feedback into motion commands while regulating interaction loads across ev

HERO: Histology Encoder for Robust Representation in Oncology

model-releasesarxiv-cs-cv

arXiv:2609.35943v1 Announce Type: new Abstract: Foundation models trained on large pathology image corpora now provide strong, transferable representations for computational pathology. Over the past f

Hybrid Ensemble Learning for EEG-Based Epileptic Seizure Forecasting

arXiv:2609.35876v1 Announce Type: new Abstract: Epileptic seizure forecasting aims to provide actionable warnings before seizure onset, yet patient-independent generalization and false-alarm control r

Information-theoretic receding-horizon active learning of nonlinear dynamical systems

arXiv:2609.36712v1 Announce Type: cross Abstract: Accurately learning nonlinear dynamics from a finite-duration experiment requires the efficient collection of informative data. We address this challe

KUPAS MASTER: Distilling the Tacit Expertise of Master Practitioners into Agent-Ready Experience Corpora

arXiv:2609.37673v1 Announce Type: new Abstract: Experienced professionals know more than just facts and conclusions. They know which cues matter, why a judgment is reasonable, and which action to take

safetyarxiv-cs-ai

Learned Compression of SAR Phase-History Data: A Rate-Honest Feasibility Study on GOTCHA

arXiv:2609.35848v1 Announce Type: new Abstract: On-board compression of synthetic aperture radar (SAR) phase history is bandwidth-critical, and block-adaptive quantization (BAQ) remains the operationa

local-aiarxiv-cs-lg

Look Closer: Patch-wise Supervision for AI-Generated Image Detection

arXiv:2609.37937v1 Announce Type: new Abstract: How much of an image does a detector need to see? Small RGB regions can retain useful evidence of image synthesis even when they reveal little of the fu

local-aiarxiv-cs-cv

MAADBench: The Refreshable Paradigm for Anomaly Detection in Multi-Agent Systems

arXiv:2609.36556v1 Announce Type: new Abstract: Recent studies report that LLM-based multi-agent systems (MAS) fail at rates of 41%-87%, yet to our knowledge, no benchmark to date supports systematic

Applications

Making Cross-Continental Federated Learning Repeatable with FLIP: a Multi-Application Study

arXiv:2609.36001v1 Announce Type: cross Abstract: Federated learning (FL) in healthcare remains challenging, as the overhead of rebuilding governance guarantees for every collaboration stops most proj

applicationsarxiv-cs-cv

Mara Chain: Rethinking Failure as a Stepping Stone for AI System Auto-Evolution

arXiv:2609.35855v1 Announce Type: cross Abstract: Optimizing deployed AI systems increasingly amounts to editing prompts, skills, harnesses, and code rather than model weights. Existing approaches com

MatToolBench: Benchmarking Multimodal Agents in Real-World Materials Science Workflows

arXiv:2609.37053v1 Announce Type: new Abstract: Multimodal GUI agents have achieved impressive results on general software benchmarks, yet their ability to operate professional scientific software rem

Tutorials

MemEvo: Automatic Discovery of Streaming Video Memory Mechanisms

arXiv:2609.36581v1 Announce Type: new Abstract: Query-agnostic streaming video understanding requires vision-language models to continuously compress an indefinitely growing visual stream into a bound

tutorialsarxiv-cs-ai

Meta-learning accelerates detector design optimization

arXiv:2609.35827v2 Announce Type: cross Abstract: The quality of a detector design is ultimately determined by the quality of the inference it enables, that is, by the accuracy with which the quantiti

Minkowski Attractor Networks: Closed-Form Hyperbolic Flows for Visual Representations

arXiv:2609.37817v1 Announce Type: new Abstract: Geometric representation learning predominantly scaffolds representations onto flat Euclidean subspaces or compact product tori (T^K). However, flat man

researcharxiv-cs-cv

Agents

Monocular 3D Occupancy Perception for Robots on Sidewalks via Hybrid 2D-3D Learning

arXiv:2606.19122v2 Announce Type: replace Abstract: Sidewalks in the real world are crowded, cluttered, and less structured than roads, making 3D occupancy prediction a key ingredient for the safe nav

agentsarxiv-cs-ro

More Features Are Not More Evidence: Limits of Training-Free Human Activity Recognition with Jev

arXiv:2609.36154v1 Announce Type: new Abstract: General-purpose models promise sensor-based decisions without training a task-specific classifier, which could reduce the dependence of Human Activity R

Tutorials

More Programs or More Rolls? Separating Coverage from Specialization in LLM Harnesses

arXiv:2609.35873v1 Announce Type: new Abstract: Automated generation of LLM harnesses promises to improve inference through task specialization. Yet additional answer coverage can arise from repeated

tutorialsarxiv-cs-ai

MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learning

arXiv:2609.37384v1 Announce Type: new Abstract: Molecular representation learning is central to computer-aided drug discovery. Molecular graphs, SMILES strings, and 3D conformations provide complement

Multi-task learning for the automatic grading of enlarged perivascular space burden using MRI

arXiv:2609.37387v1 Announce Type: new Abstract: Enlarged perivascular spaces (PVS) visible in brain magnetic resonance imaging (MRI) are increasingly thought to be linked to poor brain health. PVS are

local-aiarxiv-cs-cv

Applications

MultiTalk: Scaling Full-Duplex Speech Models to Long, Multi-Party, Bilingual Conversation

arXiv:2609.36903v1 Announce Type: cross Abstract: End-to-end full-duplex speech models have brought open-source machine conversation closer to human-like interaction, yet existing systems remain limit

applicationsarxiv-cs-ai

On Calibration of Large Language Models: From Response To Capability

arXiv:2602.13540v2 Announce Type: replace-cross Abstract: Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on

One Readout, Many Repairs: Diffusion-Guided Hierarchical Search for Tool-Agent Repair

arXiv:2609.34879v2 Announce Type: replace Abstract: Tool agents use large language models to act through external tools, yet successfully executed calls can still leave user requests unfulfilled. Tool

PHASE: A Physiology-Guided Hierarchical Foundation Model for Intracranial EEG

arXiv:2609.36087v1 Announce Type: cross Abstract: Clinicians and neuroscientists have long analyzed intracranial electroencephalography (iEEG) through directly measurable physiological characteristics