Search: “benchmark”

Sandwich-Residuals: Parameter-Efficient Test-time Adaptation of World Models

arXiv:2609.21740v1 Announce Type: new Abstract: Latent world models enable planning by predicting the effects of actions in a learned representation space, but their predictions can become unreliable

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Model Releases

Scaling Discovery through Test-Time Communication

DGX agent

arXiv:2609.21032v1 Announce Type: cross Abstract: Science advances not in isolation but through collaboration, yet existing agentic systems capture little of this. Whether communicating agents help re

model-releasesarxiv-cs-ai

21 Sept 2026

SignGPT: Toward LLM-Mediated Sign Language Interaction through Gloss-Free Translation and Generation

arXiv:2609.21709v1 Announce Type: new Abstract: Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to ena

SIRA: Reasoning-Aware Surgical Instrument Segmentation via Query-Anchored Alignment

arXiv:2609.21402v1 Announce Type: new Abstract: Surgical instrument segmentation (SIS) plays a critical role in robotic assistance and surgical workflow analysis. However, most existing SIS methods fo

SpecOpt: Contact-Diff Reasoning for Agentic Molecule Optimization Toward Binding Specificity

arXiv:2609.21165v1 Announce Type: new Abstract: Off-target protein binding is a major source of adverse effects for small-molecule drugs, yet most structure-based molecular design methods focus on gen

Local Ai

SpecQuant: Speculative Decoding with Multi-Parent Quantization for Adaptive LLM Inference

arXiv:2609.21704v1 Announce Type: new Abstract: Running large language models (LLMs) locally continues to be limited by restrictions of compute and memory on consumer hardware. The popular acceleratio

local-aiarxiv-cs-lg

SynthDemo-RL: Breaking the Zero-Reward Barrier in VLA Adaptation with LLM-Guided Synthetic Demonstrations

arXiv:2609.21650v1 Announce Type: cross Abstract: Fine-tuning Vision-Language-Action (VLA) models commonly relies on human teleoperation demonstrations, while reinforcement learning (RL) with sparse b

The Hidden Cost of Digits: Number Normalization and WER in ASR Systems

arXiv:2609.21084v1 Announce Type: cross Abstract: Modern automatic speech recognition (ASR) systems trained on extremely large datasets can produce transcripts with numbers written in Arabic numerals.

researcharxiv-cs-cl

The Stochastic Shift: A New Evaluation Paradigm for Text-to-SQL with AI Operators

arXiv:2609.21133v1 Announce Type: cross Abstract: SQL has been augmented with AI operators, enabling modern data analytics platforms to derive insights from both structured and unstructured data. We o

researcharxiv-cs-ai

Think Locally, Refine Globally for Memory-Efficient 3D Reconstruction

arXiv:2609.21437v1 Announce Type: cross Abstract: We propose LoG-VGGT, a memory-efficient framework for long-sequence 3D reconstruction that balances local temporal modeling with global camera consist

researcharxiv-cs-ai

Time series generation with spectrally aligned latent flow matching

arXiv:2609.21989v1 Announce Type: new Abstract: Latent flow models have proven to be a reliable and cost-effective method for time series generation. However, the latent compression induces unwanted a

Towards Effective Visual-Inertial SLAM with Passive-Only Sensors for Low-Cost Autonomous Underwater Vehicles

arXiv:2609.21015v1 Announce Type: new Abstract: Improvements to Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) for low-cost autonomous underwater vehicles (AUVs) are critical for tran

Towards Secure Cloud-Native Computing: Unveiling Kubernetes Misconfigurations with Large Language Models

arXiv:2609.20834v1 Announce Type: new Abstract: In the rapidly evolving landscape of cloud-native computing, Organizations are increasingly adopting infrastructure models that emphasize scalability, f

Towards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation

arXiv:2603.16086v2 Announce Type: replace-cross Abstract: While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts o

Tracing the Evidence Behind Zero-Shot Time-Series Forecasting: A Source-First Taxonomy and Audit Framework

arXiv:2609.21425v1 Announce Type: new Abstract: Zero-shot time-series forecasting (TSF) is often described as forecasting without target-specific parameter updates, but that training-status condition

Uncertainty-driven training for three-dimensional calibrated lung nodule classification

arXiv:2609.20905v1 Announce Type: cross Abstract: In this work, we present an uncertainty-driven training framework for three-dimensional computed tomography (CT) lung nodule classification, where val

VGGT-CAD: Reconstructing Parametric CAD 3D Model with Geometric Grounding

arXiv:2609.21225v1 Announce Type: new Abstract: Parametric CAD reconstruction requires recovering both precise geometry and editable modeling operations from visual observations, making it challenging

VQ-Logits: Compressing the Output Bottleneck of Large Language Models via Vector Quantized Logits

arXiv:2505.10202v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable success but face significant computational and memory challenges, particularly due to their ex

When Should a Failing Robot Ask? Initiating Corrective Human-Robot Dialogue from Audited Sensor Evidence

arXiv:2609.21942v1 Announce Type: cross Abstract: A robot that fails at a task faces the first decision in corrective dialogue: act on its own diagnosis, consult another onboard sensor, or interrupt a

A Noise Optimum in Rehearsal-Free Continual Learning: Isolation, Mechanism, and Scope

arXiv:2609.20162v1 Announce Type: new Abstract: Injecting stochastic noise into a consolidation rule can improve a network's retention of earlier tasks up to an optimal level, then degrade it -- an in

safetyarxiv-cs-lg

AgentPProf: Semantic Profiler for Long Horizon AI Agents

arXiv:2609.20301v1 Announce Type: new Abstract: AI agents increasingly orchestrate long-running activities with users, tools, and system resources for days and weeks. To improve agent quality, safety,

safetyarxiv-cs-ai

AgriScope: Pixel-Grounded Multimodal Understanding for Agricultural Images

arXiv:2609.20325v1 Announce Type: new Abstract: Agricultural image understanding requires fine-grained recognition of plant diseases, pests, crop structures, and botanical species under complex real-w

Tutorials

Bayesian Optimization with Rich Auxiliary Information via LLMs

arXiv:2609.19437v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely used for optimizing expensive black-box functions, yet many real-world optimization problems contain substantially

tutorialsarxiv-cs-lg

Before the Warning Comes Too Late: Incremental Phone-Scam Detection from Speech

arXiv:2609.20223v1 Announce Type: new Abstract: We study weakly supervised incremental telecom fraud detection from raw telephone audio, where training provides only conversation-level labels and pred

Boreas Road Trip: A Multi-Sensor Autonomous Driving Dataset on Challenging Roads

arXiv:2602.16870v2 Announce Type: replace Abstract: The Boreas Road Trip (Boreas-RT) dataset extends the multi-season Boreas dataset to new and diverse locations that pose challenges for modern autono

Can 4D Foundation Models Remember?

arXiv:2609.20819v1 Announce Type: new Abstract: Perceiving and remembering the visual world is fundamental to navigating and interacting with our environment. Current 4D foundation models, such as cam

researcharxiv-cs-cv

Can Vision-Language Models Judge Olympic Diving? From Reasoning to Scores in Zero-Shot Action Quality Assessment

arXiv:2609.19354v1 Announce Type: cross Abstract: Automated action quality assessment (AQA) in Olympic sports remains a challenging task due to the complexity of human motion and the subjectivity inhe

CitySTAR: Structured and Topology-Aware Reasoning for Open-Vocabulary Urban 3D Grounding

arXiv:2609.19911v1 Announce Type: new Abstract: 3D grounding aims to localize target entities in complex scenes from natural language and plays a fundamental role in embodied perception and spatial re

ClashBench: Conflicts Leading Agents to Seize and Harm

arXiv:2609.19892v1 Announce Type: cross Abstract: As agent systems become more widely used, multiple agent sessions increasingly run alongside pre-existing user tasks in the same environment, sharing

CliniCIRCA: A Modular LLM Framework for Constructing Longitudinal Mental Health Patient Journeys from Raw EHR Narratives

arXiv:2609.19585v1 Announce Type: cross Abstract: In mental health care, reasoning over patient journeys is a key task for clinicians. Yet these journeys, encompassing a longitudinal progression of bi

Compact Vision Models for Iris Presentation Attack Detection under Presentation Attack Instrument Shift and Environmental Degradation

arXiv:2609.20386v1 Announce Type: new Abstract: Iris presentation attack detection (PAD) is security-critical when a subsystem that appears reliable during development encounters presentation attack i

COMPASS: Ordered Clustered Routing at 100K Scale

arXiv:2609.20352v1 Announce Type: new Abstract: Large-scale routing often requires visiting clusters of nodes in a prescribed order, giving rise to the Ordered Clustered Traveling Salesman Problem (OC

researcharxiv-cs-lg

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

Applications

Compositional Reasoning in Language Models under Reinforcement Learning Post-Training

arXiv:2609.19465v1 Announce Type: new Abstract: Compositional reasoning is critical for real-world problem solving: since training data is necessarily limited, models must generalize by composing lear

applicationsarxiv-cs-ai

Contagion on the Trading Floor: How Adversarial Signals Spread in Multi-Agent Trading Systems

arXiv:2609.19789v1 Announce Type: new Abstract: Multi-agent trading systems built on large language models (LLMs) are beginning to appear in quantitative finance, yet their robustness to adversarial i

CoRe: Coherence and Relational Alignment for Multivariate Time Series Forecasting

arXiv:2609.19670v1 Announce Type: new Abstract: Direct forecasting has become a standard paradigm for multivariate time-series forecasting because it predicts the full future horizon in a single pass.

safetyarxiv-cs-lg

Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning

arXiv:2609.20461v1 Announce Type: cross Abstract: Studying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are

Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication

arXiv:2609.19531v1 Announce Type: cross Abstract: We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for mul

researcharxiv-cs-ai

Diagnose, Recover, Certify: Task Readiness under Hidden Dynamics Changes

arXiv:2609.20304v1 Announce Type: new Abstract: A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the pol

safetyarxiv-cs-ai

Dictionary-Constrained Grapheme-to-Phoneme for Unsegmented Languages from LLM-Annotated Data

arXiv:2609.19805v1 Announce Type: new Abstract: Grapheme-to-phoneme (G2P) conversion turns raw text into its phonemic form and is an essential part of both text-to-speech (TTS) and automatic speech re

Elastic Spectral State Space Models for Train-Once Budgeted Inference

arXiv:2601.22488v3 Announce Type: replace Abstract: Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms wi

EmbodiedMind: Adaptive Data Curation and Prefix-Tree Reinforcement Learning for Efficient Embodied Intelligence

arXiv:2609.19659v1 Announce Type: cross Abstract: Training embodied foundation models typically requires massive-scale datasets and extensive computational resources, yet often suffers from three crit

Equivariant Filter Design for Acoustic and Depth Aided Inertial Navigation Systems

arXiv:2609.19742v1 Announce Type: new Abstract: Autonomous Underwater Vehicles (AUVs) navigating without GPS typically fuse inertial measurements with acoustic Doppler Velocity Log (DVL) velocities an

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon whereby users are exposed to a limited and narrow

FASA: Feedback-Aware Sampling Adaptation for Efficient Diffusion-Based VLA Models

arXiv:2609.19475v1 Announce Type: new Abstract: Diffusion-based Vision-Language-Action (VLA) models achieve strong performance in embodied tasks, but their iterative sampling imposes heavy computation

researcharxiv-cs-ro

FCA-Guided Counterfactual Explanations for Multi-Modal Breast Cancer Diagnosis: A Framework Achieving Perfect Validity with Emergent Sparsity

arXiv:2609.20067v1 Announce Type: new Abstract: Deep learning models for multi-modal breast cancer diagnosis achieve high predictive accuracy but remain clinically unacceptable without actionable, cou

FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction

arXiv:2609.20026v1 Announce Type: new Abstract: Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial c

FreqDINO++: A Frequency-Guided Multi-Task Routing Vision Foundation Model for Universal Ultrasound Analysis

arXiv:2609.20340v1 Announce Type: new Abstract: Ultrasound image analysis plays a crucial role in cancer screening and prenatal diagnosis, yet comprehensive assessment requires jointly addressing task