Search: “benchmark”

Mixture of Experts for Low-Resource LLMs

model-releasesarxiv-cs-cl

arXiv:2605.17598v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures enable efficient model scaling, yet expert routing behavior across underrepresented languages remains poorly unde

MorphSeek: Fine-grained Latent Representation-Level Policy Optimization for Deformable Image Registration

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DGX agent

arXiv:2511.17392v3 Announce Type: replace Abstract: Deformable image registration (DIR) remains a fundamental yet challenging problem in medical image analysis, largely due to the prohibitively high-d

model-releasesarxiv-cs-cv

19 May 2026

Multi-Party Multi-Objective Optimization as Consensus Search: Runtime Analysis of Cross-Party Recombination

arXiv:2605.17454v1 Announce Type: new Abstract: Multi-party multi-objective optimization problems (MPMOPs) require consensus among autonomous decision makers and therefore differ from flattened many-o

Multi-site PPG: An In-the-Wild Physiological Dataset from Emerging Multi-site Wearables

arXiv:2605.17859v1 Announce Type: cross Abstract: Wearables are widely used for mobile health monitoring, and photoplethysmography (PPG) is a key sensing modality for heart rate and related physiologi

Natural-Language Agent Harnesses

arXiv:2603.25723v2 Announce Type: replace-cross Abstract: Agent performance is strongly shaped by the surrounding harness: the external execution system around a model that organizes a task run. Yet t

Neuroscience-inspired Staged Representation Learning with Disentangled Coarse- and Fine-Grained Semantics for EEG Visual Decoding

arXiv:2605.16923v1 Announce Type: new Abstract: Decoding visual information from electroencephalography (EEG) signals remains a fundamental challenge in brain-computer interfaces and medical rehabilit

Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density

arXiv:2605.17340v1 Announce Type: new Abstract: Time series foundation models rely on large-scale pretraining over diverse datasets across domains, yet their heterogeneity in temporal patterns could h

researcharxiv-cs-lg

Online Resource Allocation with Convex-set Machine-Learned Advice

arXiv:2306.12282v2 Announce Type: replace-cross Abstract: Decision-makers often have access to machine-learned predictions about future demand that can help guide online resource allocation decisions.

OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention

arXiv:2605.06088v2 Announce Type: replace Abstract: Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semanti

researcharxiv-cs-cv

OpenJarvis: Personal AI, On Personal Devices

arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local

OPERA: A Reinforcement Learning--Enhanced Orchestrated Planner-Executor Architecture for Reasoning-Oriented Multi-Hop Retrieval

arXiv:2508.16438v4 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) and dense retrievers have driven significant progress in retrieval-augmented generation (RAG).

Agents

OProver: A Unified Framework for Agentic Formal Theorem Proving

arXiv:2605.17283v1 Announce Type: cross Abstract: Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely i

agentsarxiv-cs-ai

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

arXiv:2605.16363v1 Announce Type: new Abstract: Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective

Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels

arXiv:2509.02351v3 Announce Type: replace-cross Abstract: Labeled data is a fundamental component in training supervised deep learning models for computer vision tasks. However, the labeling process,

Orthologic for SAT Solving

arXiv:2605.16421v1 Announce Type: cross Abstract: We present a new algorithm for deciding formula entailment in orthologic (a sound approximation of classical logic) that avoids the costly preprocessi

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

arXiv:2605.18587v1 Announce Type: cross Abstract: Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin

Parallel Recursive LSTM

arXiv:2605.17108v1 Announce Type: new Abstract: Transformers have become the dominant architecture for sequence modeling by using self-attention to enable expressive and highly parallel processing. Ho

researcharxiv-cs-lg

Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

arXiv:2605.17719v1 Announce Type: new Abstract: CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dep

researcharxiv-cs-cv

Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign

arXiv:2605.16452v1 Announce Type: cross Abstract: Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiog

Perception-based Image Denoising via Generative Compression

arXiv:2602.11553v2 Announce Type: replace-cross Abstract: Image denoising aims to remove noise while preserving structural details and perceptual realism, yet distortion-driven methods often produce o

PERL: Parameter Efficient Reasoning in CLIP Latent Space

arXiv:2605.18464v1 Announce Type: new Abstract: Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by aligning images and text in a shared embedding space. How

Tutorials

PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning

arXiv:2601.08679v3 Announce Type: replace Abstract: As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can

tutorialsarxiv-cs-ai

PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting

arXiv:2605.16449v1 Announce Type: cross Abstract: Deep forecasting models often suffer from attenuated periodic perception and entangled trend-noise representations as network depth increases. Moreove

PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics

arXiv:2605.18303v1 Announce Type: cross Abstract: World models built on recurrent state space architectures enable efficient latent imagination, yet remain physically unstructured, producing dynamics

Physics-Guided Geometric Diffusion for Macro Placement Generation

arXiv:2605.16451v1 Announce Type: cross Abstract: Macro placement is a pivotal stage in VLSI physical design, fundamentally determining the overall chip performance. Recent data-driven placement metho

Position: Age Estimation Models Do Not Process Biometric Data

arXiv:2605.17347v1 Announce Type: cross Abstract: When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative

safetyarxiv-cs-cv

Position: AI Evaluations Should be Grounded on a Theory of Capability

arXiv:2509.19590v2 Announce Type: replace Abstract: Evaluations of generative models are now ubiquitous, and their outcomes critically shape public and scientific expectations of AI's capabilities. Ye

Agents

Position: Universal Time Series Foundation Models Rest on a Category Error

arXiv:2602.05287v2 Announce Type: replace Abstract: This position paper argues that the pursuit of 'Universal Foundation Models for Time Series' rests on a fundamental category error, mistaking a stru

agentsarxiv-cs-ai

Post-Trained MoE Can Skip Half Experts via Self-Distillation

arXiv:2605.18643v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) scales language models efficiently through sparse expert activation, and its dynamic variant further reduces computation by a

Predictive Prefetching for Retrieval-Augmented Generation

arXiv:2605.17989v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves factual grounding in large language models but suffers from substantial latency due to synchronous retri

Preference Instability in Reward Models: Detection and Mitigation via Sparse Autoencoders

arXiv:2605.16339v1 Announce Type: new Abstract: Preference learning in large language models relies on reward models as proxies for human judgment. However, these models frequently exhibit preference

researcharxiv-cs-lg

Prefix-Adaptive Block Diffusion for Efficient Document Recognition

arXiv:2605.16861v1 Announce Type: cross Abstract: Block Diffusion Models (BDMs) support parallel generation, flexible-length output, and KV caching, making them promising for efficient document parsin

Presupposition and Reasoning in Conditionals: A Theory-Based Study of Humans and LLMs

arXiv:2605.18352v1 Announce Type: new Abstract: Presupposition projection in conditionals is central to theories of meaning and pragmatics, yet it remains largely unevaluated in large language models.

safetyarxiv-cs-cl

ProtoFlow: Mitigating Forgetting in Class-Incremental Remote Sensing Segmentation via Low-Curvature Prototype Flow

arXiv:2604.03212v2 Announce Type: replace Abstract: Remote sensing segmentation in real deployment is inherently continual: new semantic categories emerge, and acquisition conditions shift across seas

researcharxiv-cs-cv

PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting

arXiv:2605.16793v1 Announce Type: new Abstract: Time series forecasting under non-stationarity faces a fundamental tension between capturing stable representations and adapting to distribution shifts.

safetyarxiv-cs-lg

QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting

arXiv:2605.18333v1 Announce Type: cross Abstract: Accurate and efficient time-series forecasting remains a challenging problem for both classical and quantum neural architectures, particularly in mult

Applications

QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction

arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake signals. While classical deep learning models such

applicationsarxiv-cs-lg

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2512.19134v2 Announce Type: replace Abstract: Dynamic Retrieval-Augmented Generation adaptively determines when to retrieve during generation to mitigate hallucinations in large language models

Query-Aware Learnable Graph Pooling Tokens as Prompt for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2501.17549v2 Announce Type: replace Abstract: Graph-structured data plays a vital role in numerous domains, such as social networks, citation networks, commonsense reasoning graphs and knowledge

Rad-VLSM: A Cross-Modal Framework with Semantics-Assisted Prompting for Medical Segmentation and Diagnosis

arXiv:2605.18130v1 Announce Type: new Abstract: Medical image segmentation is more clinically valuable when it supports diagnosis rather than merely producing lesion masks. However, diagnostically rel

safetyarxiv-cs-cv

Radial-Angular Geometry for Reliable Update Diagnosis in Noisy-Label Learning

arXiv:2605.17429v1 Announce Type: cross Abstract: Noisy-label methods often estimate sample reliability from forward-space signals such as loss, confidence, or entropy. These signals indicate whether

Tutorials

RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture

arXiv:2601.15891v2 Announce Type: replace Abstract: Recent advances in medical vision language models guide the learning of visual representations; however, this form of supervision is constrained by

tutorialsarxiv-cs-cv

Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation

arXiv:2605.18591v1 Announce Type: cross Abstract: Natural policy gradients improve optimization by accounting for the geometry of distribution space, but their practical use is limited by the cost of

Ranking-Aware Calibration for Reliable Multimodal Reinforcement Learning

arXiv:2605.16999v1 Announce Type: new Abstract: Reinforcement learning post-training has substantially improved the reasoning accuracy of vision-language models, yet the resulting policies remain poor

safetyarxiv-cs-lg

Local Ai

RAPT: Retrieval-Augmented Post-hoc Thresholding for Multi-Label Classification

arXiv:2605.16535v1 Announce Type: cross Abstract: Industrial multi-label document understanding pipelines score candidate labels and threshold or rank them to form a label set per document. This early

local-aiarxiv-cs-ai

RAVE: Re-Allocating Visual Attention in Large Multimodal Models

arXiv:2605.18359v1 Announce Type: new Abstract: Large multimodal models (LMMs) inherit the self-attention mechanism of pretrained language backbones, yet standard attention can exhibit suboptimal allo

safetyarxiv-cs-cv

Reasoning Before Diagnosis: Physician-Inspired Structured Thinking for ECG Classification

arXiv:2605.17308v1 Announce Type: new Abstract: Electrocardiogram (ECG) diagnosis in clinical practice relies on structured reasoning over multiple hierarchical aspects, including cardiac rhythm, cond

ReBaR: Reference-Based Reasoning for Robust Pose Estimation from Monocular Images

arXiv:2303.11675v3 Announce Type: replace Abstract: R}easoning for Robust Human Pose and Shape Estimation), designed to estimate human body shape and pose from single-view images. ReBaR effectively ad