Search: “benchmark”

Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

arXiv:2407.09016v2 Announce Type: replace Abstract: Object-oriented embodied navigation tasks require agents to locate specific objects, either defined by category or images, in unseen environments. W

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Research

OpenCoF: Learning to Reason Through Video Generation

DGX agent

arXiv:2607.08763v1 Announce Type: cross Abstract: Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video g

researcharxiv-cs-ai

10 Jul 2026

path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting

arXiv:2607.07935v1 Announce Type: cross Abstract: We present path_boost, a Python package for interpretable supervised learning on graph-structured input data. The package implements PathBoost, a grad

PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-scale Physics Simulations

arXiv:2607.08025v1 Announce Type: new Abstract: While neural PDE solvers have demonstrated significant potential for accelerating engineering simulations, existing architectures remain constrained by

local-aiarxiv-cs-lg

PIT-SUN: A Deployable Empirical Marginal Transform Framework with Expectation-Consistent Recovery for Regression in Recommender Systems

arXiv:2607.08202v1 Announce Type: new Abstract: Estimating original-space conditional expectations is central to value-driven recommender systems, including dwell time, GMV, and LTV forecasting. Stand

researcharxiv-cs-lg

PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

arXiv:2607.08269v1 Announce Type: new Abstract: Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML. We prese

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

arXiv:2607.08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose est

PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation

arXiv:2510.19475v2 Announce Type: replace Abstract: Monocular 3D human pose estimation remains a fundamentally ill-posed inverse problem due to the inherent depth ambiguity in 2D-to-3D lifting. While

Psychological Competence as a Missing Dimension in AI Evaluation

arXiv:2607.08285v1 Announce Type: new Abstract: Current AI evaluation frameworks focus primarily on technical performance, including accuracy, robustness, reasoning ability, and policy compliance. The

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

RetailBench: Evaluating Long-Horizon Autonomous Decision-Making and Strategy Stability of LLM Agents in Realistic Retail Environments

arXiv:2603.16453v3 Announce Type: replace Abstract: Large language model (LLM) agents have made rapid progress on short-horizon, well-scoped tasks, yet their ability to sustain coherent decisions in d

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

arXiv:2601.22588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as reference-free evaluators via prompting, but this 'LLM-as-a-Judge' paradigm is costly, opaque,

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting

arXiv:2607.08234v1 Announce Type: cross Abstract: Real-world time series exhibit complex dynamics characterized by multiple simultaneous temporal patterns: short-term fluctuations, periodic seasonal c

local-aiarxiv-cs-ai

Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration

arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages

safetyarxiv-cs-cl

Applications

SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation

arXiv:2607.08246v1 Announce Type: new Abstract: We study 4D generation to synthesize temporally coherent sequences of 3D geometry for animation and content creation. In contrast to existing SDS-based

applicationsarxiv-cs-cv

SkillPlug: Unsupervised Skill Mining for Few-Shot Adaptation in Robotic Manipulation

arXiv:2607.08354v1 Announce Type: new Abstract: Learning transferable visuomotor imitation policies that generalize across diverse manipulation tasks and adapt rapidly to new tasks from only a handful

safetyarxiv-cs-ro

Spectral Stability of Pseudoinverse-Based Extreme Learning Machine

arXiv:2607.08581v1 Announce Type: new Abstract: Extreme Learning Machine (ELM) computes output weights analytically using the Moore-Penrose pseudoinverse. Although this leads to fast training, its num

researcharxiv-cs-lg

SPHINX: First Explain, Then Explore

arXiv:2606.17482v2 Announce Type: replace Abstract: Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent a

safetyarxiv-cs-cv

Applications

StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling

arXiv:2507.05240v2 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low

applicationsarxiv-cs-cv

SwinIFS: Landmark Guided Swin Transformer For Identity Preserving Face Super Resolution

arXiv:2601.01406v2 Announce Type: replace-cross Abstract: Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to

The Phasor Transformer: Resolving Attention Bottlenecks on the Unit Circle

arXiv:2603.17433v2 Announce Type: replace-cross Abstract: Transformer models have redefined sequence learning, yet dot-product self-attention introduces a quadratic token-mixing bottleneck for long-co

TMI: Text-to-Image Meets Image-to-Image for Complementary Data Synthesis to Boost Long-Tailed Instance Segmentation

arXiv:2607.08201v1 Announce Type: cross Abstract: Large-vocabulary instance segmentation is constrained by long-tailed category distributions and fine-grained inter-class ambiguity. While data synthes

TNODEV: Toolbox for Neural ODE Verification

arXiv:2606.16567v2 Announce Type: replace Abstract: Neural ordinary differential equations (neural ODE) gained attention in safety critical settings such as continuous-time controllers for cyber-physi

safetyarxiv-cs-ai

TOPO-Bench: An Open-Source Topological Mapping Evaluation Framework with Quantifiable Perceptual Aliasing

arXiv:2510.04100v2 Announce Type: replace-cross Abstract: Topological mapping offers a compact and robust representation for navigation, but progress in the field is hindered by the lack of standardiz

Training and Evaluating Diffusion Policies with Long Context Lengths

arXiv:2606.16447v2 Announce Type: replace-cross Abstract: Imitation learning has enabled highly-dexterous robotic manipulation from RGB observations. Policies trained with these methods, however, typi

Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning

arXiv:2602.23440v4 Announce Type: replace Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to interleave reasoning with search engine calls. How

researcharxiv-cs-cl

TVTA: Trajectory-Aware Viseme-Guided Temporal Aggregation for Event-Based Lip Reading

model-releasesarxiv-cs-cv

arXiv:2607.08236v1 Announce Type: new Abstract: Event-based lip reading has recently emerged as a promising direction for visual speech recognition, benefiting from the high temporal resolution and mo

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio

model-releasesarxiv-cs-cv

arXiv:2607.08127v1 Announce Type: new Abstract: Generative video foundation models exhibit strong compositional priors, yet world-action models (WAMs) and video-action models (VAMs) often lose these p

Applications

Unpaired Joint Distribution Modeling via Multi-Scale Image Representations

arXiv:2607.08198v1 Announce Type: new Abstract: This paper studies the problem of learning a joint distribution from marginal observations, which is inherently ill-posed due to the ambiguity of feasib

applicationsarxiv-cs-cv

Validity of LLMs as data annotators: AMALIA on authority

arXiv:2607.08731v1 Announce Type: cross Abstract: A national language model offers a linguistic community its own instrument for measuring what its citizens say and value. Portugal's AMALIA, a publicl

Vision-Language Memory for Spatial Reasoning

arXiv:2511.20644v2 Announce Type: replace Abstract: Spatial reasoning is a critical capability for intelligent robots, yet current vision-language models (VLMs) still fall short of human-level perform

Wat3R: Underwater 3D Geometry Learning without Annotations

arXiv:2607.08772v1 Announce Type: new Abstract: Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

arXiv:2607.08375v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition o

When Debiasing Backfires: Counterintuitive Side Effects of Preprocessing-Based Stereotype Mitigation

arXiv:2607.07937v1 Announce Type: new Abstract: Preprocessing-based methods for stereotype mitigation, such as pre-/post-training on debiased corpora, are widely used in NLP. While these approaches re

researcharxiv-cs-cl

Agents

When Does Continual Learning Require Learning

arXiv:2607.07847v1 Announce Type: new Abstract: As large language models (LLMs) become increasingly capable, the next question is how can we enable models to continually learn? Today, the field largel

agentsarxiv-cs-lg

When Implausible Tokens Get Reinforced: Tail-Aware Credit Calibration for LLM Reinforcement Learning

arXiv:2607.07976v1 Announce Type: cross Abstract: Reinforcement learning (RL) has achieved remarkable success in enhancing the reasoning capabilities of large language models (LLMs). However, widely u

Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems

arXiv:2607.07989v1 Announce Type: cross Abstract: Large language model (LLM) based multi-agent systems enable complex problem solving through coordinated reasoning and action, but their distributed st

local-aiarxiv-cs-ai

ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device

arXiv:2607.08771v1 Announce Type: new Abstract: Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational dem

Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning

arXiv:2607.07708v1 Announce Type: cross Abstract: Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge

Tutorials

An Edge-aware Prompt-enhanced SAM for Ultrasound Image Segmentation

arXiv:2607.07240v1 Announce Type: new Abstract: Ultrasound image segmentation is essential for delineating anatomical structures and lesions, providing the foundation for accurate diagnosis. While the

tutorialsarxiv-cs-cv

AnchorPrune: Relevance-Anchored Contextual Expansion for Visual Token Pruning

arXiv:2607.07033v1 Announce Type: cross Abstract: Large vision-language models incur substantial inference costs because high-resolution inputs introduce thousands of visual tokens, many of which are

local-aiarxiv-cs-ai

ASFR-Net: Adversarial Alignment and Spatio-Frequency Refinement Network for Heterogeneous Remote Sensing Image Change Detection

model-releasesarxiv-cs-cv

arXiv:2607.07161v1 Announce Type: new Abstract: The core challenge of heterogeneous change detection in remote sensing imagery lies in effectively decoupling genuine land-cover changes from significan

Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass

arXiv:2607.07696v1 Announce Type: cross Abstract: Analytical workloads operating on data stored in external database systems face a fundamental bottleneck: data access is guarded entirely by the datab

BubbleSH: A Dataset of Rising Bubbles with Deformable Interfaces

model-releasesarxiv-cs-lg

arXiv:2607.07275v1 Announce Type: new Abstract: Bubbly flows exhibit complex multiscale dynamics, with deformable bubbles interacting through the surrounding liquid and giving rise to strongly coupled

BUS: Brain-Inspired Unsupervised Self-Reflection for Advanced Multimodal Reasoning

arXiv:2607.07361v1 Announce Type: new Abstract: Current Vision-Language Models (VLMs) often struggle to handle complex visual tasks that require consistent and fine-grained reasoning. Recent methods a

ButterflyMoE: Compression-Scalable Ternary Experts via Structured Butterfly Orbits

arXiv:2601.13563v5 Announce Type: replace-cross Abstract: In current Mixture of Experts (MoE) architectures, linear memory scaling is present, the memory grows as the number of experts increases. N in

C-DeltaTheta: Circuit-Restricted Weight Arithmetic for Selective Refusal

arXiv:2602.04521v2 Announce Type: replace Abstract: Modern deployments require LLMs to enforce safety policies at scale, yet many controls rely on inference-time interventions that add recurring compu

local-aiarxiv-cs-cl

Calibration-Family Overfit: Why Trusted Sabotage Monitors Don't Transfer Across Lineages

model-releasesarxiv-cs-lg

arXiv:2607.06596v1 Announce Type: cross Abstract: Trusted monitoring is a central defense in AI control: a cheaper trusted model scores an untrusted model's actions for sabotage, and the most suspicio