Search: “benchmark”

FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly comprom

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Applications

GazeVLA: Learning Human Intention for Robotic Manipulation

DGX agent

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

27 Apr 2026

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

agentsarxiv-cs-cl

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair

arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen

researcharxiv-cs-ai

How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining

arXiv:2511.18903v2 Announce Type: replace-cross Abstract: Due to the scarcity of high-quality data, large language models (LLMs) are often trained on mixtures of data with varying quality levels, even

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

arXiv:2508.05633v2 Announce Type: replace-cross Abstract: Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interacti

LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs

arXiv:2602.17681v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent s

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs

arXiv:2604.22050v1 Announce Type: cross Abstract: Transformers are mostly relying on softmax attention, which introduces quadratic complexity with respect to sequence length and remains a major bottle

Learning Coverage- and Power-Optimal Transmitter Placement from Building Maps: A Comparative Study of Direct and Indirect Neural Approaches

arXiv:2604.22056v1 Announce Type: new Abstract: Optimal wireless transmitter placement is a central task in radio-network planning, yet exhaustive search becomes prohibitively expensive at scale. This

Learning from Natural Language Feedback for Personalized Question Answering

arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se

Applications

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa

applicationsarxiv-cs-ai

LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines

arXiv:2411.08027v3 Announce Type: replace-cross Abstract: Most learning-based approaches to complex physical reasoning sidestep the crucial problem of parameter identification (e.g., mass, friction) t

LLMs as Assessors: Right for the Right Reason?

model-releasesarxiv-cs-cl

arXiv:2601.08919v2 Announce Type: replace-cross Abstract: A good deal of recent research has focused on how Large Language Models (LLMs) may be used as judges in place of humans to evaluate the qualit

Long-tail Internet photo reconstruction

arXiv:2604.22714v1 Announce Type: new Abstract: Internet photo collections exhibit an extremely long-tailed distribution: a few famous landmarks are densely photographed and easily reconstructed in 3D

Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents

arXiv:2604.22085v1 Announce Type: new Abstract: The transition from stateless language model inference to persistent, multi session autonomous agents has revealed memory to be a primary architectural

agentsarxiv-cs-ai

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

arXiv:2604.21937v1 Announce Type: new Abstract: Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specializ

MTT-Bench: Predicting Social Dominance in Mice via Multimodal Large Language Models

arXiv:2604.22492v1 Announce Type: cross Abstract: Understanding social dominance in animal behavior is critical for neuroscience and behavioral studies. In this work, we explore the capability of Mult

OccDirector: Language-Guided Behavior and Interaction Generation in 4D Occupancy Space

arXiv:2604.22240v1 Announce Type: new Abstract: Generative world models increasingly rely on 4D occupancy for realistic autonomous driving simulation. However, existing generation frameworks depend on

OmniOVCD: Streamlining Open-Vocabulary Change Detection with SAM 3

arXiv:2601.13895v2 Announce Type: replace-cross Abstract: Change Detection (CD) is a fundamental task in remote sensing. It monitors the evolution of land cover over time. Based on this, Open-Vocabula

researcharxiv-cs-ai

Optimal sequential decision-making for error propagation mitigation in digital twins

arXiv:2604.22168v1 Announce Type: new Abstract: Here, we explore the problem of error propagation mitigation in modular digital twins as a sequential decision process. Building on a companion study th

PAGaS: Pixel-Aligned 1DoF Gaussian Splatting for Depth Refinement

arXiv:2604.22129v1 Announce Type: new Abstract: Gaussian Splatting (GS) has emerged as an efficient approach for high-quality novel view synthesis. While early GS variants struggled to accurately mode

researcharxiv-cs-cv

PoseFM: Relative Camera Pose Estimation Through Flow Matching

arXiv:2604.22350v1 Announce Type: new Abstract: Monocular visual odometry (VO) is a fundamental computer vision problem with applications in autonomous navigation, augmented reality and more. While de

agentsarxiv-cs-cv

Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization

arXiv:2604.22345v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong implicit personalization ability, yet most existing approaches treat this behavior as a black box, relying o

Tutorials

PrivSTRUCT: Untangling Data Purpose Compliance of Privacy Policies in Google Play Store

arXiv:2604.22157v1 Announce Type: cross Abstract: Existing research typically treats privacy policies as flat, uniform text, extracting information without regard for the document's logical hierarchy.

tutorialsarxiv-cs-ai

Region Matters: Efficient and Reliable Region-Aware Visual Place Recognition

arXiv:2604.22390v1 Announce Type: new Abstract: Visual Place Recognition (VPR) determines a query image's geographic location by matching it against geotagged databases. However, existing methods stru

Regularized Meta-Learning for Improved Generalization

arXiv:2602.12469v2 Announce Type: replace Abstract: Deep ensemble methods often improve predictive performance, yet they suffer from three practical limitations: redundancy among base models that infl

Relaxation-Informed Training of Neural Network Surrogate Models

arXiv:2604.22746v1 Announce Type: cross Abstract: ReLU neural networks trained as surrogate models can be embedded exactly in mixed-integer linear programs (MILPs), enabling global optimization over t

ReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation

arXiv:2604.22546v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible relation phrases beyond a fixed predicate set. Existing method

researcharxiv-cs-cv

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

arXiv:2604.22180v1 Announce Type: cross Abstract: Large language model (LLM) based listwise reranking has emerged as the dominant paradigm for achieving state-of-the-art ranking effectiveness in infor

Rethinking Publication: A Certification Framework for AI-Enabled Research

arXiv:2604.22026v1 Announce Type: new Abstract: AI research pipelines now produce a growing share of publishable academic output, including work that meets existing peer-review standards for quality a

Robust Localization for Autonomous Vehicles in Highway Scenes

arXiv:2604.22040v1 Announce Type: new Abstract: Localization for autonomous vehicles on highways remains under-explored compared to urban roads, and state-of-the-art methods for urban scenes degrade w

agentsarxiv-cs-ro

Score-based Membership Inference on Diffusion Models

arXiv:2509.25003v2 Announce Type: replace-cross Abstract: Membership inference attacks (MIAs) against Diffusion Models (DMs) raise pressing privacy concerns by revealing whether a sample was part of t

SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMs

model-releasesarxiv-cs-cl

arXiv:2604.22134v1 Announce Type: new Abstract: Large Language Models (LLMs) have been widely explored in educational scenarios. We identify a critical vulnerability in current educational LLMs, pedag

Hardware

Soft Anisotropic Diagrams for Differentiable Image Representation

arXiv:2604.21984v1 Announce Type: new Abstract: We introduce Soft Anisotropic Diagrams (SAD), an explicit and differentiable image representation parameterized by a set of adaptive sites in the image

hardwarearxiv-cs-cv

Sovereign Agentic Loops: Decoupling AI Reasoning from Execution in Real-World Systems

arXiv:2604.22136v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly issue API calls that mutate real systems, yet many current architectures pass stochastic model outputs

Spend Less, Fit Better: Budget-Efficient Scaling Law Fitting via Active Experiment Selection

arXiv:2604.22753v1 Announce Type: new Abstract: Scaling laws are used to plan multi-million-dollar training runs, but fitting those laws can itself cost millions. In modern large-scale workflows, asse

STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation

arXiv:2604.22282v1 Announce Type: new Abstract: Knowledge Graph-based Question Answering (KGQA) plays a pivotal role in complex reasoning tasks but remains constrained by two persistent challenges: th

Sum-of-Checks: Structured Reasoning for Surgical Safety with Large Vision-Language Models

arXiv:2604.22156v1 Announce Type: cross Abstract: Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectomy is essential to prevent bile duct injury, a comp

Toward Automated Robustness Evaluation of Mathematical Reasoning

model-releasesarxiv-cs-cl

arXiv:2506.05038v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in various reasoning-intensive tasks. However, these models exhibit unexpecte

Safety

Towards Safe Mobility: A Unified Transportation Foundation Model enabled by Open-Ended Vision-Language Dataset

arXiv:2604.22260v1 Announce Type: cross Abstract: Urban transportation systems face growing safety challenges that require scalable intelligence for emerging smart mobility infrastructures. While rece

safetyarxiv-cs-ai

TreeCoder: Systematic Exploration and Optimisation of Decoding and Constraints for LLM Code Generation

arXiv:2511.22277v2 Announce Type: replace Abstract: Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when

Universal Transformers Need Memory: Depth-State Trade-offs in Adaptive Recursive Reasoning

arXiv:2604.21999v1 Announce Type: cross Abstract: We study learned memory tokens as computational scratchpad for a single-block Universal Transformer (UT) with Adaptive Computation Time (ACT) on Sudok

UR^2: Unify RAG and Reasoning through Reinforcement Learning

arXiv:2508.06165v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong capabilities through two complementary paradigms: Retrieval-Augmented Generation (RAG) for know

Safety

When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models

arXiv:2510.21285v4 Announce Type: replace Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harm

safetyarxiv-cs-ai

Where Should LoRA Go? Component-Type Placement in Hybrid Language Models

arXiv:2604.22127v1 Announce Type: new Abstract: Hybrid language models that interleave attention with recurrent components are increasingly competitive with pure Transformers, yet standard LoRA practi

A Dynamic Framework for Grid Adaptation in Kolmogorov-Arnold Networks

arXiv:2601.18672v3 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) have recently demonstrated promising potential in scientific machine learning, partly due to their capacity for gr

24 Apr 2026

A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization

arXiv:2604.21411v1 Announce Type: new Abstract: Standard physics-informed neural networks (PINNs) struggle to simulate highly oscillatory Helmholtz solutions in heterogeneous media because pointwise m

24 Apr 2026

A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking

arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi