Search: “benchmark”

Prototype Matters: Modality-unified Prototype Self-distillation for Unsupervised Visible-infrared Person Re-identification

arXiv:2609.11514v1 Announce Type: new Abstract: Estimating reliable cross-modality association is crucial to unsupervised visible-infrared person re-ID. While optimal transport is shown to be a practi

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Quantifying Logical Consistency in Transformers via Query-Key Alignment

DGX agent

arXiv:2502.17017v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive performance in various natural language processing tasks, yet their ability to perform multi

safetyarxiv-cs-ai

11 Sept 2026

RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation

arXiv:2609.11648v1 Announce Type: new Abstract: Multivariate time series imputation (MTSI) aims to recover missing values in temporal data composed of multiple interdependent variables. This problem i

ReGround: Grounding Reviewer Comments in Multimodal Evidence

arXiv:2609.11460v1 Announce Type: new Abstract: Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to

Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSIC

arXiv:2609.09409v1 Announce Type: cross Abstract: Near-field localization is a promising technique for high-resolution multi-user positioning in future wireless systems, but its performance is often d

Tutorials

Rethinking Handwritten Character Recognition

arXiv:2609.10572v1 Announce Type: new Abstract: Non-Latin handwritten character recognition (HCR) remains understudied. Dominant methods consider it as generic image classification, which uses model s

tutorialsarxiv-cs-cv

REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving

arXiv:2609.11209v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive large language model (LLM) applications by conditioning generation on retrieved docu

RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion for Multimodal Prediction under Modality Uncertainty

arXiv:2609.10798v1 Announce Type: cross Abstract: Image-metadata prediction requires fusing heterogeneous evidence whose reliability can vary across samples and latent factors. Existing representation

Robust Multimodal Sentiment Analysis with Incomplete Modalities via Semantic-aware Completeness based Reconstruction

model-releasesarxiv-cs-cl

arXiv:2609.10950v1 Announce Type: new Abstract: Recent multimodal sentiment analysis studies increasingly adopt text-centric fusion approaches to exploit the rich sentiment information inherent in the

SearchAtlas: Analyzing Agentic Search Strategies via Evidential Query Graphs

arXiv:2609.10901v1 Announce Type: new Abstract: LLM search agents are often evaluated on final-answer accuracy, overlooking the process. Analyzing a search strategy requires understanding how credible

agentsarxiv-cs-cl

SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data

arXiv:2412.16078v2 Announce Type: replace Abstract: Improving the reliability and completeness of colonoscopic inspection is critical for reducing missed lesions and improving colorectal cancer preven

SG-Blend: Learning an Interpolation Between Improved Swish and GELU for Robust Neural Representations

arXiv:2505.23942v2 Announce Type: replace Abstract: Prevailing activation functions such as Swish and GELU tend toward domain-specific optima, Swish was discovered via neural architecture search on vi

safetyarxiv-cs-lg

Solving Few-Shot Multiobjective Multitask Optimization via Iterative Sequential Transfer

arXiv:2609.11228v1 Announce Type: new Abstract: Applying knowledge transfer across multiple optimization tasks, multitask optimization (MTO) emerges as a promising approach to solving synergistic opti

Spec-Harness: Measuring and Improving Behavioral Adequacy of LLM-Synthesized Formal Specifications

arXiv:2604.00280v2 Announce Type: replace-cross Abstract: Formal specifications play a central role in ensuring software reliability, yet automatically synthesizing high-quality specifications remains

Structural priors for data-efficient language learning

model-releasesarxiv-cs-cl

arXiv:2609.11505v1 Announce Type: new Abstract: Efficient language learning requires methods to reduce the reliance on large data and computational resources. We investigate structural transfer: First

Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters

arXiv:2501.12299v3 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

arXiv:2609.11414v1 Announce Type: new Abstract: Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing

Symmetry-aware super-resolution of crystal orientation maps via invariant latent-space learning

arXiv:2609.10898v1 Announce Type: new Abstract: Crystal-orientation maps are physical fields defined only up to crystal symmetry; electron backscatter diffraction (EBSD) resolves them experimentally,

T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

arXiv:2609.11042v1 Announce Type: new Abstract: Agent usage is shifting toward long-horizon tasks such as coding and scientific discovery, among which terminal tasks are especially important. We intro

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

arXiv:2609.11838v1 Announce Type: new Abstract: Cardiovascular screening models trained on national health surveys routinely report areas under the receiver operating characteristic curve (AUROC) near

safetyarxiv-cs-cl

The Platonic brain bridge hypothesis: human brain networks as an architectural prior for omni models

arXiv:2609.10947v1 Announce Type: cross Abstract: We propose the Platonic brain bridge hypothesis: omni models, which process video, audio and text jointly like the brain, converge on brain-like repre

The widening evaluation gap in medical large language model research 2023 to 2026

arXiv:2609.11770v1 Announce Type: new Abstract: Large language models are superseded every few quarters; clinical evidence takes years. We asked whether medical research is keeping pace with the syste

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

model-releasesarxiv-cs-cl

arXiv:2609.10745v1 Announce Type: new Abstract: Multimodal entity linking grounds entity mentions in text and images to knowledge-base entries. These systems degrade on rare entities, but prior work m

Thinking that we’ll get safety by CoT traces is wishful thinking. Safety lives in the harness, not the chain of thought

Astra's launch has produced a strange discourse. The reporting that broke the story framed the model's use of recurrent depth primarily as a safety regression, because it means the model reveals less

safetyr-localllama

Toward Interpretable Multimodal Fusion: Heat Conduction Modeling for Hyperspectral and LiDAR Joint Classification

arXiv:2609.11040v1 Announce Type: new Abstract: The fusion of hyperspectral (HS) and Light Detection and Ranging (LiDAR) data plays a crucial role in enhancing land-cover classification by jointly exp

Tri-DehazeGS: Scene--Medium Decoupled Gaussian Splatting with Transmittance-Aware Optimization

arXiv:2609.11223v1 Announce Type: new Abstract: Recovering clean 3D scenes from hazy multi-view images is challenging because haze attenuates scene radiance and introduces atmospheric scattering. Rece

Two-Parameter Flow Map Learning for Continuous-Time Diffeomorphic Image Registration

arXiv:2609.10789v1 Announce Type: new Abstract: Diffeomorphic image registration is central to medical image analysis, enabling anatomically consistent alignment across subjects. Most learning-based d

V-Retrver: Evidence-Driven Agentic Reasoning for Universal Multimodal Retrieval

arXiv:2602.06034v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have recently been applied to universal multimodal retrieval, where Chain-of-Thought (CoT) reasoning improv

agentsarxiv-cs-cv

What Language is This? Ask Your Tokenizer

arXiv:2602.17655v3 Announce Type: replace Abstract: Language Identification (LID) is an important component of many multilingual natural language processing pipelines, where it facilitates corpus cura

When do cheap embeddings beat protein language models? A theoretically-grounded hashing sketch for biological sequence classification

arXiv:2512.10147v2 Announce Type: replace Abstract: extbf{Motivation:} Pre-trained protein language models (PLMs) such as ESM-2 have become the default representation for biological sequence tasks, bu

When is Test-Time Adaptation Identifiable From Unlabeled Evidence?

arXiv:2609.11235v1 Announce Type: new Abstract: Test-time adaptation (TTA) offers many ways to update a deployed model without labels, but choosing the wrong update can make a strong source model wors

When Synthetic Data Hurts: On Catastrophic Forgetting in Skill Retrieval for LLM Agents

arXiv:2609.10750v1 Announce Type: cross Abstract: LLM agents increasingly rely on external skills retrieved at runtime, making skill selection from large repositories a critical challenge. We present

Which Tokens Should SFT Actually Learn? A Token-Trimming Perspective on Mathematical Reasoning

arXiv:2609.09707v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) applies a uniform cross-entropy loss to all target tokens, even though different tokens provide unequal learning signals fo

Why Sample What You Can Enumerate? Exact Policy Optimization for Genomic Tool Selection

arXiv:2609.10221v2 Announce Type: new Abstract: Reinforcement learning over a frozen reasoner has become a common recipe for teaching a policy which external tools to invoke. We show that this recipe

safetyarxiv-cs-ai

XAI-Arena: Can LLMs Assess the Quality of XAI Explanations?

arXiv:2609.09428v1 Announce Type: new Abstract: Evaluating the quality of explanations produced by explainable AI (XAI) methods remains challenging because existing approaches often rely on subjective

Applications

Xiaomi-CocktailASR-1 Technical Report

arXiv:2609.11274v1 Announce Type: cross Abstract: Recently, large language model (LLM) based ASR models have achieved significant progress, yet they generally lack support for multi-speaker scenarios,

applicationsarxiv-cs-cl

A Minimum-Energy Control Approach for Redundant Mobile Manipulators in Physical Human-Robot Interaction Applications

model-releasesarxiv-cs-ro

arXiv:2603.25259v2 Announce Type: replace Abstract: Research on mobile manipulation systems that physically interact with humans has expanded rapidly in recent years, opening the way to tasks which co

A practical DIRECT-type algorithm for medium-scale black-box global optimization

arXiv:2609.09796v1 Announce Type: new Abstract: The DIRECT algorithm is a deterministic global optimization method known for its versatility and balanced exploration-exploitation strategy. However, DI

Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground

arXiv:2609.09257v1 Announce Type: new Abstract: Sensor-based AI systems are rarely operated under the conditions under which they were trained: devices, personnel and recording epochs change, and each

researcharxiv-cs-lg

Adaptive Shared Control with Online Bounded-Rational Human Behavior Estimation

model-releasesarxiv-cs-ro

arXiv:2609.10215v1 Announce Type: new Abstract: This work considers adaptive shared human-robot control for nonlinear control-affine systems, where the assumption of a fully rational human is relaxed

Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending

arXiv:2609.09945v1 Announce Type: new Abstract: Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where appli

AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems

arXiv:2609.08572v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) achieve strong performance by employing specialized multiple agents, yet their performance de

agentsarxiv-cs-ai

Agentic Algorithm Engineering: Improving Shared-Memory Exact Minimum Cuts

arXiv:2609.07204v1 Announce Type: new Abstract: The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weighted sum of th

Agentic Electronic Design Automation: A Handoff Perspective

arXiv:2606.19795v2 Announce Type: replace-cross Abstract: Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools.

agentsarxiv-cs-ai

Albedo Estimation via Latent Bridge Matching

arXiv:2609.09884v1 Announce Type: new Abstract: Recent advances in Intrinsic Image Decomposition (IID) have increasingly relied on generative models. However, progress remains limited by three key cha

Algorithmic Optimality Guarantees for Nonsmooth H_infty Output-Feedback Policy Search

arXiv:2609.06197v1 Announce Type: cross Abstract: We study continuous-time full-order dynamic output-feedback H_infty policy search, a nonconvex and nonsmooth problem. Direct policy search is a centra

AlignDiff: Exploiting Model-Intrinsic Information for Better Preference Data Selection

arXiv:2609.05899v1 Announce Type: cross Abstract: Aligning large language models with human preferences remains a challenge, primarily due to the critical role of preference data quality in effective

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models

arXiv:2506.10633v2 Announce Type: replace Abstract: Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent years. In the domain of natural (RGB) images, recent