Search: “benchmark”

arXiv:2610.13028v1 Announce Type: new Abstract: Neural operators that learn physical laws from data should generalize beyond their training distribution and expose the learned law in closed form. The

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MADS: Multi-Agent Dialog Simulation for Robust Conversational Agents

DGX agent

arXiv:2610.12757v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under realistic conditions, especially when users exhibit non-cooperative behavior. Existing function

model-releasesarxiv-cs-cl

12 Oct 2026

NovaSplat: Model-Free 6D Object Pose Estimation via 3D Gaussian Splatting Onboarding and Refinement

model-releasesarxiv-cs-ro

arXiv:2610.13309v1 Announce Type: cross Abstract: 6D pose estimation of novel objects without CAD models remains an open challenge: model-free methods must build the object representation from scratch

Oido: Open-Vocabulary Speech Recognition on a $5 Microcontroller without a Neural Accelerator

arXiv:2610.13447v1 Announce Type: cross Abstract: Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oido, an inferenc

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

Scaling RNA Foundation Models through Iterative Refinement

arXiv:2610.13106v1 Announce Type: new Abstract: Biological function in RNA is encoded across scales, from local sequence motifs to long-range structural dependencies. Conventional RNA foundation model

Tutorials

SpatialASM: Internalizing Active Mentalization for Spatial Reasoning

arXiv:2610.13832v1 Announce Type: cross Abstract: When solving complex spatial reasoning tasks, ordinary humans naturally revisit the scenes from task-relevant viewpoints and mentally reconstruct the

tutorialsarxiv-cs-ai

TabReliBench: Evaluating Tabular Foundation Models Beyond Predictive Accuracy

arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions

Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf

arXiv:2610.13036v1 Announce Type: new Abstract: Evaluating deep learning optimizer is challenging because confounding factors such as hyperparameter tuning and optimizer-model co-design often obscure

A mesh-based neural energy method for the simulation of heterogeneous composites

arXiv:2610.10862v1 Announce Type: cross Abstract: Modeling heterogeneous materials remains a challenge for physics-informed neural networks such as the deep energy method (DEM). The DEM and its varian

Accurate and Efficient Object Pose Estimation via the Aggregation of Diffusion Features

arXiv:2403.18791v4 Announce Type: replace Abstract: Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very l

Adapting English Quality Classifiers for Multilingual LLM Pretraining Data Selection

arXiv:2610.11585v1 Announce Type: cross Abstract: Recent advances in large language model (LLM) pretraining highlight the role of high-quality training data in improving performance. While model-based

AgentHorizon: Evaluating Agentic Judges for Long-Horizon Computer-Use Tasks

arXiv:2610.11050v1 Announce Type: new Abstract: Computer-use agents are capable of completing complex tasks, increasing the use of automatic judges to determine success, either for training or for eva

BEANS-Next and ROOTS: Broadening Audio-Language Capabilities for Bioacoustics

arXiv:2610.10663v1 Announce Type: cross Abstract: Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-lang

Closed-loop evaluation of LLM agents for embedded software development

arXiv:2610.11447v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as coding agents that edit files, run builds and tests, inspect execution results, and repair s

Evaluating Local Language Model Agents for Reproducible Data Engineering: An Empirical Software Engineering Study of Mobility Workflows

arXiv:2610.11482v1 Announce Type: cross Abstract: Context: Large language model (LLM) agents are increasingly used as software and data-engineering assistants, yet evidence about locally deployable op

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

arXiv:2510.00536v2 Announce Type: replace Abstract: Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. How

Large Language Model Turnover Undermines Screening for Artificial Intelligence-Assisted Scientific Writing

arXiv:2610.11599v1 Announce Type: cross Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this scree

Learning to Orchestrate Evolutionary Search: Progression-Aware Deep Reinforcement Learning for Dynamic DE-CMA-ES Coordination in Optimization and Structural Model Updating

arXiv:2610.11546v1 Announce Type: cross Abstract: Solving high-dimensional structural model updating problems requires an algorithm capable of navigating complex, non-convex landscapes with correlated

Research

Less from More: Reinforcing Sparse Video Reasoning from Dense References

arXiv:2610.10893v1 Announce Type: new Abstract: Video-language models commonly assume that more temporal observations lead to more reliable reasoning. We question this assumption and argue that the ke

researcharxiv-cs-cv

LLM-IDEA: Identifiability-Driven Experimental Agent for Autonomous Discovery of Mechanistic World Models

arXiv:2610.11253v1 Announce Type: new Abstract: Large language model agents are being increasingly deployed as autonomous scientists, designing experiments and inferring mechanistic world models with

MemTrial: Learning When to Trust Memory in LLM Portfolio Agents

arXiv:2610.11732v1 Announce Type: new Abstract: Large language model (LLM) agents for portfolio management learn from experience: they credit each experience in their memory with the outcome of the de

Research

MotherTree: Meta-learning on synthetic data improves decision tree training

arXiv:2610.10832v1 Announce Type: new Abstract: Conventional decision tree algorithms produce effective, transparent models that can be audited, communicated, and deployed independently of the trainin

researcharxiv-cs-lg

Neural Networks for Temporal Pattern Recognition and Dynamic Arm Gesture Speed Estimation for Robot Control

arXiv:2610.11631v1 Announce Type: cross Abstract: Deploying intelligent robotic systems that interact with humans through gestures requires neural networks capable of recognizing diverse temporal patt

Agents

One Skill Too Many: How Co-Installed Skills Conflict in Coding Agents

arXiv:2610.11647v1 Announce Type: cross Abstract: Coding agents are extended with agent skills, directories whose SKILL.md tells the model when and how to perform a task. Because skills come from inde

agentsarxiv-cs-ai

Agents

OneSearch-VL: Unified Multimodal Deep Research Agent for Image and Video

arXiv:2610.12419v1 Announce Type: new Abstract: Single-image, multi-image, and video deep research require different visual operations but share a workflow of visual grounding, external retrieval, and

agentsarxiv-cs-cv

Perception Test 2026: Challenge Summary and Extension to City-scale Audio-Visual Reasoning

arXiv:2610.12081v1 Announce Type: new Abstract: Continuing the Perception Test challenge series, we organised the fourth edition as a workshop at the European Conference on Computer Vision (ECCV) 2026

Reconstruction of Multiscale Plasma Dynamics Across Operating Regimes

arXiv:2610.11004v1 Announce Type: cross Abstract: Reconstructing spatially resolved plasma dynamics from few sensors is essential for diagnostics, reduced-order modelling and control, yet remains diff

RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees

arXiv:2610.11370v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) grounds language models in external corpora. Agentic RAG enables iterative search, yet exposes the model to isolate

SteerablePlex: Can We Steer Full-Duplex Models?

arXiv:2610.12201v1 Announce Type: cross Abstract: Full-duplex speech models can listen and speak simultaneously, enabling natural interaction, but become increasingly difficult to control as the conve

StoreBench: A Live-Commerce Environment for Evaluating and Training Autonomous Operator Agents

arXiv:2610.10942v1 Announce Type: new Abstract: Reinforcement learning environments are now a primary lever for improving large language model (LLM) capabilities in post-training, yet most agentic ben

Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits

arXiv:2610.12005v1 Announce Type: new Abstract: Which forms of test-time compute improve the predictions of strong pretrained tabular foundation models (TFMs)? We systematically study this along three

WARP-VLA: Wrist-Camera Adaptation for View-Robust Policy Execution in Vision-Language-Action Models

arXiv:2610.11508v1 Announce Type: cross Abstract: Despite recent advances in Vision-Language-Action models (VLAs) for robotic manipulation, their performance remains sensitive to changes in camera con

What to Admit and How to Present: Governing Persistent Memory in LLM Agents

arXiv:2610.11188v1 Announce Type: new Abstract: Persistent memory can improve personalization in LLM agents but can also induce sycophancy and cross-domain leakage. We distinguish two governance decis

Research

Why machines will still not rule the world

arXiv:2610.11424v1 Announce Type: new Abstract: In our book Why machines will never rule the world [13, 14] we argue that arti- ficial general intelligence is mathematically impossible. This is becaus

researcharxiv-cs-ai

Workerville: Towards an Organizational Behavior Account of Agent Safety

arXiv:2610.11561v1 Announce Type: new Abstract: LLM-based agents now interact with their environments continuously, shaped by such organizational channels as user instructions, peer messages, and long

Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

Argos: Adapt Rich Geometric Priors for Generalizable Online Scene-Change-Detection

arXiv:2610.10181v1 Announce Type: new Abstract: Robots operating in dynamic environments require reliable detection of how their surroundings change over time. Existing learning-based methods largely

Autonomous Driving Research Requires a Community-Driven Data Paradigm

arXiv:2610.08825v1 Announce Type: new Abstract: Autonomous driving has made remarkable progress, with recent AI advances enabling commercial deployments that are reshaping urban mobility. Yet the fiel

Beyond Anonymous Captions: Grounding Character Identity in Video Captioning and Question Answering

arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-awa

Cache the Encoder Within:Compact, Reusable Memory across LLM Queries

arXiv:2610.10058v1 Announce Type: new Abstract: Repeated queries over shared documents incur redundant encoding, while caching model states introduces persistent storage costs. Building on CoMem's int

Tutorials

CERO: Where and When to Allocate Rollouts for RL Post-Training

arXiv:2610.09679v1 Announce Type: new Abstract: Adaptive rollout methods for group-relative reinforcement learning typically allocate a fixed per-update budget across prompts. We instead study how to

tutorialsarxiv-cs-lg

CircuitGate: Logic-Consistent Circuit-Level Functional Modeling for And-Inverter Graphs

arXiv:2610.09549v1 Announce Type: new Abstract: And-Inverter Graphs (AIGs) are fundamental representations for logic synthesis and verification in Electronic Design Automation (EDA). As structured rep

ECHO: Embodied Camera Observations of Human Object Carrying

arXiv:2610.10438v1 Announce Type: new Abstract: Embodied and assistive agents must do more than recognize objects: they must reason about where an object belongs given the layout of an environment and

EDiS: Edge Disjoint Subgraph Sparsification Framework for Graph Neural Networks

arXiv:2610.09059v1 Announce Type: new Abstract: Sparse GNN training reduces computation, but deciding which edges to keep can be costly. Reusing one sparse graph is cheap, but locks training to a fixe

FinVector-Market-4B: A Controlled Study of LoRA Adaptation for Structured Financial Tasks

arXiv:2610.08882v1 Announce Type: cross Abstract: FinVector-Market-4B adapts Qwen/Qwen3.5-4B with rank-16 LoRA on a 22,000-example corpus for structured financial tasks. We evaluate the base and adapt

From Pixel to Coding: Evaluating the Figure Reproduction Capabilities of MLLMs

arXiv:2610.10066v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in both visual understanding and code generation. However, existing b

From Uncertainty to Action: Learning to Steer LLM Agents

arXiv:2610.09115v1 Announce Type: cross Abstract: Steering an LLM agent means deciding whether to correct it, at which step, and with which mechanism. Uncertainty is often used to decide when to corre