Search: “benchmark”

HFEMCNet: A Compact Hybrid Frequency Enriched Multi Channel Network for Automatic Modulation Classification

arXiv:2609.22139v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) of received radio signals is prudent for further signal processing tasks such as communication monitoring, c

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Model Releases

Hi-Singers: A Comprehensive High-Quality Dataset for Expressive Audio-Driven Singing Head Synthesis

DGX agent

arXiv:2609.22264v1 Announce Type: cross Abstract: State-of-the-art models for audio-driven digital human generation have achieved photo-realistic results in talking-head synthesis. However, extending

model-releasesarxiv-cs-cv

22 Sept 2026

Hierarchical Prompt Learning for Hyperbolic Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstre

Highly-Efficient Differentiable Simulation for Robotics

arXiv:2409.07107v3 Announce Type: replace Abstract: Robotics simulators have improved significantly in computational speed and scalability, enabling them to generate years of simulated data for comple

Holographic generative flows with AdS/CFT

arXiv:2601.22033v2 Announce Type: replace Abstract: Holography, in the form of the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, offers a natural setting for generative modelling. Da

Hybrid Imitation Learning: Teleoperation Augmentation Primitives that Policies Learn to Trigger

arXiv:2512.04960v2 Announce Type: replace Abstract: What an operator can demonstrate bounds what imitation learning can learn. Teleoperation interfaces map the human body to the robot, so motions that

safetyarxiv-cs-ro

HyperCLIP++: Fine-tuning CLIP forOpen-vocabulary Semantic Segmentation in Hyperbolic Space

model-releasesarxiv-cs-cv

arXiv:2609.24564v1 Announce Type: new Abstract: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation. While freezing CLIP's text encoder

Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework

arXiv:2609.24556v1 Announce Type: cross Abstract: Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially h

Incentive Noise and Structural Prior Infusion for Multi-modal Object Re-Identification

arXiv:2609.24539v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) benefits from complementary information across heterogeneous imaging modalities. To further enrich semantic

safetyarxiv-cs-cv

Applications

Inductive Graph Representation Learning with Quantum Graph Neural Networks

arXiv:2503.24111v4 Announce Type: replace-cross Abstract: Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classical

applicationsarxiv-cs-lg

Information-Time Proximal Policy Optimization

arXiv:2609.24380v1 Announce Type: new Abstract: RLVR has substantially improved the reasoning capabilities of LLMs. However, existing methods typically parameterize temporal progression in the Markov

safetyarxiv-cs-lg

InsertAnything: Generalizable Contact-Rich Precision Insertion from Simulation to Reality

arXiv:2609.24511v1 Announce Type: new Abstract: Contact-rich precision insertion is a key manipulation skill in robotic assembly. Tight clearances make insertion more sensitive to alignment errors and

Tutorials

InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection

arXiv:2609.24026v1 Announce Type: new Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object dete

tutorialsarxiv-cs-cv

ITSY: Causal Discovery From Irregular Time-Series Data

arXiv:2609.23516v1 Announce Type: new Abstract: Structural causal models for time series recover contemporaneous and lagged effects, but most methods require complete observation windows and become mi

JAREX: An Acquisition Function for Multi-Objective Algorithmic Process Characterization

arXiv:2609.24954v1 Announce Type: cross Abstract: Pharmaceutical process characterization is central to Quality by Design because it defines how variations in process parameters affect the ability to

Joint Domain-Class Modeling for Federated Learning Under Feature Skew

arXiv:2609.22932v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training without centralizing private data, but performance often degrades under feature skew: clien

local-aiarxiv-cs-lg

Knowledge Graph-Augmented Ambient AI for Clinical Note Generation

arXiv:2609.22239v1 Announce Type: new Abstract: Ambient AI is increasingly adopted in healthcare to automatically generate clinical notes from patient-clinician conversations, with the potential to su

local-aiarxiv-cs-cl

KV-COBRA: KV Cache Compression via Co-Optimized Bit-Rank Allocation

arXiv:2609.24298v1 Announce Type: new Abstract: What limits KV-cache compression at extreme bit-rates? We argue that it is not the choice of compression scheme, but how its budget is allocated across

researcharxiv-cs-lg

Layer-Aware Position Embeddings for Visual Token Pruning in Multimodal Large Language Models

arXiv:2609.23715v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) incur substantial computational overhead due to the reliance on hundreds of visual tokens to represent images.

researcharxiv-cs-cv

Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

arXiv:2609.24882v1 Announce Type: new Abstract: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from hig

local-aiarxiv-cs-lg

Leveraging Inference-Time Compute for Diffusion Models via Global Scheduling of Denoising Trajectories

arXiv:2609.22867v1 Announce Type: new Abstract: Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into

Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

arXiv:2506.07044v5 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements, largely due to their lar

researcharxiv-cs-cl

List Counting Failures Are Not One Phenomenon

arXiv:2609.22230v1 Announce Type: new Abstract: Counting the items in a bracketed list looks trivial, yet open-weight chat models often get it wrong. Prior work usually blames input bottlenecks such a

LiteTex-GS: Fast and Lightweight Texturing for Gaussian Splatting

arXiv:2609.23380v1 Announce Type: new Abstract: Gaussian Splatting has enabled real-time novel view synthesis, but its tightly coupled geometry and appearance representation often require a large numb

researcharxiv-cs-cv

LLaDA-PRM: A Bidirectional Step-Level Reasoning Evaluator

arXiv:2609.22700v1 Announce Type: new Abstract: Step-level reasoning evaluators are commonly based on autoregressive language models, whose causal attention restricts each step representation to the p

LLMs Anchor on Chief Complaint and Fail to Integrate Evidence in Sequential Clinical Triage

arXiv:2609.22904v1 Announce Type: new Abstract: Triage in the emergency department (ED) is a sequential decision process that unfolds turn by turn. Existing evaluations of large language models (LLMs)

researcharxiv-cs-cl

Agents

MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback

arXiv:2606.12916v2 Announce Type: replace-cross Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle

agentsarxiv-cs-cl

ME-Brain-1.0: Memory, Cognition and Action for Evolving Embodied Intelligence

arXiv:2609.24271v1 Announce Type: new Abstract: Current embodied systems largely rely on pretrained capabilities that remain fixed after deployment, limiting their ability to learn from physical inter

local-aiarxiv-cs-ro

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

local-aiarxiv-cs-cv

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectori

MIGU: Multimodal Instruction Grounding under Uncertainty for Manipulation Planning

arXiv:2609.24995v1 Announce Type: new Abstract: Understanding natural human instructions is crucial for deploying robots in human-centric environments. We study multimodal instruction grounding, where

MiMo-V2.6-Flash on vLLM: fixes for 'empty responses' with thinking + tools, and a hidden 2,048-token output cap

model-releasesr-localllama

Some people here say MiMo-V2.6 is bad with tools and are going back to GLM-5.3-Flash. I spent today running MiMo-V2.6-Flash-RL as the backend for an agent harness, on 2× DGX Spark with vLLM, using the

Agents

MM-ContextFold: Context Folding for Multimodal Agentic Retrieval

arXiv:2609.23121v1 Announce Type: new Abstract: Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools. Typical frameworks

agentsarxiv-cs-cv

MoE-ACT: Scaling Multi-Task Bimanual Manipulation with Sparse Task-Conditioned Mixture-of-Experts Transformers

arXiv:2603.15265v2 Announce Type: replace Abstract: Developing a unified policy for multi-task robotic manipulation remains challenging due to policy degradation from task interference and negative tr

MolSC: Leveraging Substituent Contributions to Enhance Fine-grained Molecular Understanding in LLMs

arXiv:2609.23073v1 Announce Type: new Abstract: Recent advances in natural language processing have led to molecular Large Language Models (LLMs) with strong performance across diverse chemistry tasks

Monotone-Constrained Diffusion Models for Long-Horizon Production Forecasting

arXiv:2609.22643v1 Announce Type: new Abstract: Forecasting a long horizon from only the first observations of a sequence is ill-posed: many trajectories are consistent with the same short history. We

Moonworks Lunara: Modeling Artistic Intelligence

model-releasesarxiv-cs-cv

arXiv:2609.22272v1 Announce Type: new Abstract: We formulate Artistic Intelligence as exploration driven world realization, leaving space for creative possibility while preserving the semantic, artist

Multi-Armed Bernoulli Bandits via Minimax Single-Arm Stopping

arXiv:2609.22690v1 Announce Type: new Abstract: We develop an index policy for finite-horizon Bernoulli multi-armed bandits from minimax solutions to single-arm bandit (SAB) problems. Each SAB problem

Multilingual Safety Signals Are Multi-Layered: Filtering Safety-Degrading Data for Safer LLMs

arXiv:2609.22144v1 Announce Type: new Abstract: Preserving safety alignment during large language models fine-tuning is critical, however, recent studies have demonstrated that even benign fine-tuning

safetyarxiv-cs-cl

Muon Can Outperform Dedicated Continual Learning Methods

arXiv:2609.24678v1 Announce Type: cross Abstract: Continual learning with Low-Rank Adapters (LoRA) typically mitigates forgetting by penalizing the overlap between a new update and the accumulated pas

NavDreamer: Video Models as Zero-Shot 3D Navigators

arXiv:2602.09765v2 Announce Type: replace Abstract: Previous Vision-Language-Action models face critical limitations in navigation: scarce, diverse data from labor-intensive collection and static repr

NAVIR: Neuromorphic Audio-Visual Speech Recognition for Robust Human-Robot Interaction on Edge Hardware

arXiv:2609.24391v1 Announce Type: new Abstract: Voice-controlled interaction in industrial settings is hampered by acoustic noise, which severely degrades audio-only speech recognition. Audio-visual s

Negation-Aware Weighted Information Fusion for Reliable Evidential Reasoning

arXiv:2509.00754v3 Announce Type: replace Abstract: Dempster--Shafer theory (DST) provides an attractive framework for multi-source information fusion. However, its effectiveness critically depends on

OmniEdu: Open Foundation Models for Learning and Teaching

arXiv:2609.23088v1 Announce Type: new Abstract: Educational foundation models must solve problems, understand curriculum structure, diagnose learner difficulties, and provide appropriate instructional

onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction

arXiv:2609.24983v1 Announce Type: new Abstract: We present onPanda, an interactive tool for efficiently annotating LLM alignment data and agent trajectories. onPanda adopts token-level correction as i

Open Source: Ming-Image-0.1-Design family: Ming-Image-0.1-Design, 6B & Ming-Image-0.1-Design-Layer, 6B

model-releasesr-stablediffusion

Ming-Image-0.1-Design creates complete UIs, dashboards, infographics, and posters from structured prompts of up to 8K tokens, with consistent layouts, typography, colors, and imagery. It can also nati

Opinion Leader Dynamics: How Sparse Attention Shapes Token Clustering

arXiv:2609.24202v1 Announce Type: new Abstract: Sparse attention reduces the quadratic cost of global self-attention while retaining strong empirical performance, but how its restricted interactions s

ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation

arXiv:2609.23950v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition,

local-aiarxiv-cs-cv