Search: “evaluation”

arXiv:2607.08798v2 Announce Type: replace-cross Abstract: Adaptive volumetric finite element meshing traditionally requires iterative PDE solvers or heavily supervised, data-driven surrogates trained

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Grounding Deep Learning Framework Testing in Data Flow

DGX agent

arXiv:2610.15808v1 Announce Type: cross Abstract: Data flow underlies deep learning (DL) framework execution, including automatic differentiation and operator-fusion optimization. Bugs involving data

applicationsarxiv-cs-lg

14 Oct 2026

GuidanceNFT: NFT-Based Reward Fine-Tuning of Guided Diffusion Models

arXiv:2610.15856v1 Announce Type: new Abstract: DiffusionNFT (NFT) fine-tunes diffusion models toward task-specific rewards, but optimizing these rewards does not guarantee fidelity to the full prompt

HaloBlock: Faster and Better Decoding for Diffusion Large Language Models

arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.

researcharxiv-cs-lg

Harmonic Representations in Symbolic Music Transformers are Localized and Controllable

arXiv:2610.15957v1 Announce Type: cross Abstract: Transformer models trained on symbolic music have become remarkably capable. However, it is yet unclear how they represent music structure, and whethe

Applications

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat

applicationsarxiv-cs-lg

HASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation

arXiv:2610.17368v1 Announce Type: cross Abstract: Generative recommendation models have shown promising results by representing items as semantic IDs and generating these IDs autoregressively. We intr

Heading Hierarchy Reconstruction for Complex and Long Documents with Level-Wise Multimodal Memory

model-releasesarxiv-cs-cv

arXiv:2610.18238v1 Announce Type: new Abstract: Vision-language models (VLMs) have been widely adopted for document parsing and optical character recognition (OCR), as they can accurately extract page

HelpMeOut: A Neuropsychology-Grounded Benchmark for Error-Aware Monitoring of Household Task Execution

arXiv:2610.17694v1 Announce Type: new Abstract: We introduce HelpMeOut, an embodied AI benchmark for error-aware monitoring of household task execution. Existing embodied household benchmarks typicall

Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models

arXiv:2610.15781v1 Announce Type: new Abstract: Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically cons

Hierarchical Multi-Agent Reasoning Systems for Knowledge-Grounded Material Substitution

arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can

agentsarxiv-cs-lg

High-fidelity Three-Dimensional Flow Field Reconstruction Driven by Turbulent Fluid Dynamics

arXiv:2610.18045v1 Announce Type: cross Abstract: High-fidelity three-dimensional turbulent flow fields are essential for scientific and engineering analyses, yet obtaining them through direct numeric

researcharxiv-cs-lg

HodgePhaseNet: Discrete Hodge Decomposition of Semantic Flows in Transformer Attention

arXiv:2610.14971v1 Announce Type: new Abstract: WavePhaseNet introduced frequency-resolved semantic representations, QuantumPhaseNet introduced gauge-covariant phase connections, and ModularPhaseNet m

Human-Inspired Asymmetric Collaboration for Dual-Student Semi-Supervised Medical Image Segmentation

arXiv:2610.18133v1 Announce Type: new Abstract: Dual-student learning enriches predictive diversity in SSMIS by introducing a strongly augmented view alongside a weakly augmented view. Insufficient st

researcharxiv-cs-cv

Humanoid Hanoi: Investigating Shared Whole-Body Control for Skill-Based Box Rearrangement

arXiv:2602.13850v4 Announce Type: replace Abstract: We introduce Humanoid Hanoi, a challenge problem for long-horizon humanoid skill composition that requires a robot to repeatedly sequence pickup, lo

researcharxiv-cs-ro

HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning

arXiv:2610.16589v1 Announce Type: new Abstract: Electroencephalography (EEG) representation learning is challenged by noisy signals, inter-subject variability, and heterogeneous electrode montages in

Hybrid Reasoning Agents

arXiv:2610.18861v1 Announce Type: cross Abstract: How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and

agentsarxiv-cs-lg

I built BitRun: A standalone runner for 1-bit LLMs (100–127 t/s on Apple Silicon & 40–45 t/s on PC CPUs with zero compile)

model-releasesr-localllama

I built BitRun because I wanted to run 1-bit ternary LLMs on ordinary laptops without melting my battery, spinning up a dedicated GPU, or wrestling with complex build environments. Right now, BitRun g

I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation

arXiv:2610.17748v1 Announce Type: new Abstract: Policies trained offline from teleoperated demonstrations can degrade outside their training distribution. This gap is particularly acute in long-horizo

IMAGAgent: Orchestrating Multi-Turn Image Editing via Constraint-Aware Planning and Reflection

arXiv:2603.29602v2 Announce Type: replace-cross Abstract: Existing multi-turn image editing paradigms are often confined to isolated single-step execution. Due to a lack of context-awareness and close

agentsarxiv-cs-cv

Images Talk Back: Guiding MMDiTs by Suppressing Image-to-Text Feedback

arXiv:2610.13941v2 Announce Type: replace Abstract: Multimodal diffusion transformers (MMDiTs) allow the evolving image to update internal text representations through joint attention. These represent

safetyarxiv-cs-cv

Imitation Learning via Discrete and Rhythmic Primitive Composition

arXiv:2610.15639v1 Announce Type: new Abstract: Long-horizon robotic manipulation is inherently composed of semantically meaningful sub-tasks. While Movement Primitives (MPs) can model these component

Improving Neural Symbolic Regression with a Diverse Prior and Post-training Alignment

arXiv:2610.17994v1 Announce Type: new Abstract: Symbolic regression is the problem of finding an expression that fits a dataset. Solving it requires searching a combinatorial space of candidate expres

Improving Policy Learning from Delayed Interventions

arXiv:2610.17298v1 Announce Type: new Abstract: In this work, we explore the idea of expert intervention delays in human-supervised robotic systems for imitation learning system. Previous works in imi

In View or Out of View? A Vision-Aware Filter that Infers and Reacts to the Human's Field of View

arXiv:2610.14577v1 Announce Type: new Abstract: During human-robot interaction, sight plays an important role. When the human sees a robot, they can observe the robot's actions and better predict the

inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMs

arXiv:2610.18051v1 Announce Type: new Abstract: This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine

Insightful paper on recursive self-improvement with a frozen LLM. (bookmark it) Memento 3 clears every level of all 25 public ARC-AGI-3 game…

Insightful paper on recursive self-improvement with a frozen LLM. (bookmark it) Memento 3 clears every level of all 25 public ARC-AGI-3 games and uses 44% of the human action count. The underlying LLM

agentsdair-ai--x

Intent-guided Adaptive Stiffening for Visuomotor Policies under Unknown Resistance

arXiv:2610.18386v1 Announce Type: new Abstract: Manipulation tasks such as unscrewing a cap or sliding a part in contact with a surface require imposing force along a high-friction direction: the robo

Interaction Latents as Actions for Contact-Rich Manipulation

arXiv:2610.18855v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to coordinate not only where to move, but also how contact and force should evolve throughout an interaction.

Interactive 4D Volumetric Liquid Forecasting under Moving-Solid Interaction

arXiv:2610.16167v1 Announce Type: cross Abstract: We propose the task of Interactive 4D Volumetric Liquid Forecasting: predicting the spatiotemporal evolution of a future dense 3D liquid velocity fiel

Interactive Navigation Beyond Reachability: Benchmark and Agentic Framework

arXiv:2610.17089v1 Announce Type: new Abstract: Existing embodied navigation tasks commonly assume that traversability and object states remain fixed during an episode. Yet reaching a goal may require

Tutorials

Intrinsic Geometry Matching: learning observation-equivariant process geometry

arXiv:2610.16995v1 Announce Type: new Abstract: Real data are often arbitrary, indirect observations of an unknown underlying process, and those observations can distort its geometry. Existing geometr

tutorialsarxiv-cs-lg

Applications

Is Complex Query Answering Really Complex?

arXiv:2410.12537v4 Announce Type: replace Abstract: Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task. In this paper, we show that the current

applicationsarxiv-cs-lg

Japanese Handwriting Generation Based on Human Preference Feedback Using Direct Preference Optimization

arXiv:2610.14743v1 Announce Type: new Abstract: We propose a Japanese handwriting generation framework that integrates human preference feedback using Direct Preference Optimization (DPO) to align gen

researcharxiv-cs-cv

Tutorials

Just Respect the Semantics: Image-Token Compression via Pre-LLM Semantic Variable-Resolution Tokenization and In-LLM Relevance Pruning

arXiv:2610.18690v1 Announce Type: new Abstract: Image-token compression must reduce computation without hurting the semantics. We introduce Varest, guided by semantic fungibility: tokens within a cohe

tutorialsarxiv-cs-cv

KV4-RL: Unlocking Faster Asynchronous Rollouts for RLVR with INT4 KV Cache Quantization

arXiv:2610.14448v1 Announce Type: new Abstract: Asynchronous rollout improves the efficiency of reinforcement learning with verifiable rewards (RLVR) by reducing under-utilization during long-tail gen

LabInstruct: Benchmarking Situated Instructional Video Generation for Lab Procedures

arXiv:2610.14020v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) aim to automate the full experimental loop, from scientific decision-making to physical execution. Ideally, AI-generate

LABIT: Long-Horizon Robotic Assembly Benchmark for Industrial Tasks

arXiv:2610.16398v1 Announce Type: new Abstract: Robot learning has undergone significant advancements in the domain of compliant control and robotic assembly. The development of novel methodologies ha

LADDER: A Long-Horizon Robot Manipulation Benchmark

arXiv:2610.18053v1 Announce Type: cross Abstract: General-purpose robot manipulation policies learn short-horizon skills effectively, but degrade rapidly on long-horizon tasks. Existing benchmarks can

Layer-wise Input Recoverability in Deep Neural Networks

arXiv:2610.14290v1 Announce Type: new Abstract: The inner workings of deep neural networks are still not well understood. The information bottleneck framework, which characterizes deep networks by the

researcharxiv-cs-lg

Learning Dynamic Grasping

arXiv:2610.14848v1 Announce Type: new Abstract: Synthesizing believable 4D hand-object grasping sequences is important for character animation, extended reality, and embodied agents. Grasping requires

researcharxiv-cs-ro

Learning Families of Fixed-Wing Aircraft Control Policies with Hypernetwork-Conditioned Reinforcement Learning

arXiv:2604.03392v2 Announce Type: replace-cross Abstract: This paper investigates whether it is more effective to condition reinforcement learning policies across changing dynamics using standard inpu

Tutorials

Learning from fracture: Teaching language models to design through physical experience

arXiv:2610.17804v1 Announce Type: cross Abstract: How can language models learn to optimize physical designs through experience? We introduce FracLearn, an experience-abstraction-generalization framew

tutorialsarxiv-cs-lg

Learning Multimodal Sensor Fusion with JEPA Representations for Breathing Activity and Pose Recognition

model-releasesarxiv-cs-cv

arXiv:2610.15891v1 Announce Type: new Abstract: Predictive video representations do not by themselves specify how a multimodal system should handle missing sensors. We transfer frozen V-JEPA2 features

Learning Safety-Constrained Whole-Body Loco-Manipulation for Lunar Surface Operations

arXiv:2610.15486v1 Announce Type: new Abstract: Robotic systems for lunar surface operations must act autonomously and preserve their own integrity in an environment where failures are unrecoverable a

Learning to Assist: Collaborative VLAs for Implicit Human-Robot Collaboration

arXiv:2606.12475v2 Announce Type: replace Abstract: Human-robot collaboration (HRC) combines the complementary strengths of humans and robots to improve task efficiency. However, many existing collabo

Learning to See through Action: Predictive Curiosity for Robots

arXiv:2610.14302v1 Announce Type: new Abstract: Humans and animals do not learn vision from a fixed set of data: they move, interact, and learn from the visual consequences of their actions. Motivated

Learning When to Transfer: Reinforcement Learning for Carbon-Footprint Modeling in New Manufacturing Domains

arXiv:2610.18730v1 Announce Type: new Abstract: Manufacturers often need to characterize a new material, process, or product before enough operating data are available to train reliable predictive mod