Search: “models”

Single-condition neural solvers encode transferable response spaces for parametric differential equations

arXiv:2609.15432v1 Announce Type: new Abstract: Operator learning for parametric partial differential equations (PDEs) typically builds global models over prescribed domains, requiring cross-condition

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Symmetries and Singularities

DGX agent

arXiv:2609.14663v1 Announce Type: new Abstract: Deep neural networks are highly over-parameterized, and different parameter values represent the same predictive function. This makes their effective co

model-releasesarxiv-cs-lg

15 Sept 2026

Syn2Logic: End-to-End Neuromorphic Design Automation

arXiv:2608.25536v2 Announce Type: replace-cross Abstract: In this work, we propose a view on electronic Neuromorphic Design Automation (eNDA), which we see as a design automation flow that bridges com

T-LoopFormer: Token-Level Elastic-Depth Looped Transformers for Latent Reasoning With Dynamic Routing

arXiv:2609.15160v1 Announce Type: new Abstract: Looped Transformers have recently demonstrated strong performance in both reasoning and language tasks by reusing a shared set of parameters across mult

TestHallVQA: Exploring LVLMs' Document-Level Reasoning under Redundant Contexts from Scientific Exams

arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar V

Local Ai

What Makes an Efficient VLA? Navigating Action-Head Design, Scaling, and Latency

arXiv:2609.13984v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models combine a pretrained vision encoder, a language backbone, and an action head, but their relative contribution has

local-aiarxiv-cs-cv

When Can You Trust Your Synthetic Users? Diagnostics and Corrections for LLM Consumer Panels

arXiv:2609.13148v1 Announce Type: cross Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising 97% cost reductions over traditional surveys. Yet aggregate va

When does a scaling result justify a different allocation? A critical review of resource-allocation evidence for AI systems

arXiv:2609.14500v1 Announce Type: new Abstract: AI scaling studies increasingly evaluate systems that combine a pretrained model with retrieval, search, verification, tools, and interaction. Yet a hig

When Tools Get in the Way: The Effect of Unnecessary Tool Availability on LLM Answering

arXiv:2609.14157v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed with external tools that extend what they can do beyond their own knowledge. Tools help on tasks

researcharxiv-cs-cl

Why LLM Agents Collapse Without Oversight: The Enforcement Gap as the Mechanism Behind Emergence World Failures

arXiv:2609.15293v1 Announce Type: new Abstract: When Emergence World placed frontier LLM agents in an unsupervised multi-agent simulation, the results were alarming: agents committed crimes, starved,

Affective Agent: On-Device Personalized Intervention Reasoning for Wearable Systems

arXiv:2609.12322v1 Announce Type: cross Abstract: Affective computing has advanced wearable state inference, but on-device reasoning about whether, when, and how to intervene remains challenging. We p

AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems

arXiv:2609.12320v1 Announce Type: cross Abstract: Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them

AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training

arXiv:2507.01663v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a pivotal technology in the post-training phase of large language models (LLMs). Traditional task-collocated

Feature Recovery for Object Understanding After Irreversible Fire Damage

arXiv:2609.12078v1 Announce Type: new Abstract: Objects in post-fire environments often undergo irreversible physical transformations that change their geometry, material state, and visual appearance.

Safety

GRACE-DS: a Guarded Reward-guided Agent Correction Environment in Data Science

arXiv:2606.16000v3 Announce Type: replace Abstract: We introduce GRACE-DS, a Guarded Reward-guided Agent Correction Environment in Data Science for pre-deployment evaluation of LLM-powered AutoML agen

safetyarxiv-cs-cl

Applications

InRTL: Effective Intra-Inter Interaction Learning for Relational Tables

arXiv:2609.12712v1 Announce Type: new Abstract: Relational table learning has recently emerged as an important research direction for modeling multiple tables connected through primary key-foreign key

applicationsarxiv-cs-lg

Investigating Temporal Motion Features for Pose-to-Text Indian Sign Language Translation

arXiv:2609.12993v1 Announce Type: cross Abstract: We investigate the effect of pretrained T5 model scale and explicit motion features on pose-to-text Indian Sign Language Translation (SLT) for the WSL

researcharxiv-cs-cl

Meddies-PII: A Multilingual Framework for Personally Identifiable Information Extraction in Clinical De-identification

arXiv:2609.12544v1 Announce Type: new Abstract: Clinical de-identification relies on accurately identifying personally identifiable information (PII). However, manually annotated datasets are costly t

Partition-Invariant Tuning for 3D Scene Understanding

arXiv:2609.12473v1 Announce Type: new Abstract: Scene-level point cloud understanding remains challenging due to diverse geometries and spatial layouts. While pre-trained 3D point cloud foundation mod

Hardware

Performance, Efficiency and Collapse -- Advantages and Challenges in Offline Post-training of Code LLMs

arXiv:2609.11956v1 Announce Type: new Abstract: Post-training with reinforcement learning (RL) is a critical phase in the development of code-generating large language models (LLMs), as it ensures adh

hardwarearxiv-cs-lg

Temporal Recurrence Favors Fewer Layers

arXiv:2609.12531v1 Announce Type: new Abstract: In streaming tasks, recurrent models can carry latent computation across time, allowing each update to build on representations produced earlier. This r

Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems

arXiv:2603.07357v3 Announce Type: replace Abstract: Latent generative models have emerged as powerful priors for solving inverse problems. These models typically represent a class of natural signals a

UFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation

arXiv:2609.12397v1 Announce Type: new Abstract: Multi-modal image generation, particularly subject-driven customization, has garnered growing attention in recent years. Despite the rapid advancement o

What Did the MLLM Hear? Token-Level Spectro-Temporal Grounding for Audio MLLM Explainability

arXiv:2609.12663v1 Announce Type: cross Abstract: Audio-based Multimodal Large Language Models (MLLMs) can generate detailed natural-language descriptions of complex acoustic scenes, yet it remains un

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

arXiv:2603.15976v2 Announce Type: replace Abstract: While LLMs have accelerated scientific code generation, comprehensively evaluating generated code remains challenging. Many benchmarks emphasize fun

12 Sept 2026

MAPLE: Memory-Augmented Planning with Language and Evolution

arXiv:2609.11636v1 Announce Type: new Abstract: Domain practitioners understand their business constraints but may lack operations-research expertise or dedicated support. LLM-based optimization agent

12 Sept 2026

What a Random Draw from the MCP Registry Contains, and What Tool-Use Benchmarks Contain Instead

arXiv:2609.10962v1 Announce Type: cross Abstract: Studies of the Model Context Protocol (MCP) server ecosystem draw their samples in ways that quietly select for servers that work: reference sets, pop

12 Sept 2026

Aerodynamic Prior-Free Coordinated Trajectory Generation and Tracking Control for a Tail-Sitter UAV

model-releasesarxiv-cs-ro

arXiv:2609.11698v1 Announce Type: new Abstract: This paper presents a coordinated trajectory generation and tracking control framework for a tail-sitter unmanned aerial vehicle (UAV), which does not r

Hardware

Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System

arXiv:2609.10922v1 Announce Type: new Abstract: Auto-research agents have shown the potential to automate hypothesis generation, experiment execution, and iterative refinement. However, scaling this p

hardwarearxiv-cs-cl

Automatic Lyric Transcription for Greek Songs: Scaling and Task Composition Effects in Whisper Adaptation

arXiv:2609.11302v1 Announce Type: new Abstract: Automatic Lyric Transcription (ALT) remains substantially more challenging than speech recognition due to melodic variability, rhythmic irregularity, an

Applications

Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditions

arXiv:2609.11126v1 Announce Type: new Abstract: Verification and validation (V&V) of classification models is crucial to enable a wide range of sensor processing applications. Currently, the V&V proce

applicationsarxiv-cs-cv

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

arXiv:2601.15397v3 Announce Type: replace-cross Abstract: The rapid emergence of new entities -- driven by cultural shifts, evolving trends, and personalized user data -- poses a significant challenge

BiHDTrans: binary hyperdimensional transformer for efficient multivariate time series classification

arXiv:2509.24425v2 Announce Type: replace Abstract: The proliferation of Internet-of-Things (IoT) devices has led to an unprecedented volume of multivariate time series (MTS) data, requiring efficient

CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation

arXiv:2609.10943v1 Announce Type: new Abstract: The integration of large language models (LLMs) into video generation has enabled rapid text-to-video creation and improved visual quality. However, it

Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

arXiv:2609.11141v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate structured outputs, but their reliability remains unclear when those outputs must satisfy

CMNIE: An Information Extraction Benchmark for Chinese Military News

arXiv:2609.10722v1 Announce Type: new Abstract: Structured extraction from Chinese military news supports intelligence analysis, decision-making, and knowledge base construction. However, existing res

Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data

arXiv:2603.21235v2 Announce Type: replace-cross Abstract: Nonrigid registration is conventionally divided into point set registration, which aligns sparse geometries, and image registration, which ali

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

arXiv:2609.10421v1 Announce Type: cross Abstract: Background: Emergency Department (ED) return visits are commonly reviewed for quality assurance, but are often limited (e.g., to revisits within 48-72

Fast and Accurate Monomodal 3D High Resolution Deep Registration of Drosophila Larval Brain Volumes

arXiv:2609.11240v1 Announce Type: new Abstract: The larval stage of Drosophila melanogaster is a compact model system for neuroscience whose genetic toolkit allows fluorescent markers to be expressed

From Cycle Space to Cycle Manifold: Limits and Achievability of Blind False Data Injection Attacks

arXiv:2609.10631v1 Announce Type: cross Abstract: A false data injection attack (FDIA) can change the estimated grid state while evading a residual-based bad data detector (BDD). Existing blind attack

HuRo: Robotizing Human Videos for Scalable VLA Pretraining

arXiv:2609.10706v1 Announce Type: cross Abstract: Human video datasets have emerged as a compelling alternative to expensive real-robot data, offering rich diversity at scale. To bridge the human-to-r

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

arXiv:2609.09324v1 Announce Type: cross Abstract: Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the chan

Learning structural balance of graphs from quantum spectral features

arXiv:2609.11736v1 Announce Type: cross Abstract: We develop a quantum approach to spectral feature extraction from the density of states (DOS) of a problem-dependent Hamiltonian, and apply it to mach

LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents

arXiv:2609.09754v1 Announce Type: new Abstract: As large language models are increasingly deployed as tool-augmented legal agents, they introduce agentic hallucinations where tool-call and reasoning e

MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning

arXiv:2609.10545v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed model training without centralizing data but suffers from high communication overhead. To address this, we

Numbat: Building and Verifying a Self-Contained Machine-Learning Stack

arXiv:2609.10632v1 Announce Type: cross Abstract: Machine-learning systems are built almost exclusively on a few large Python-orchestrated frameworks, and they inherit those stacks' engineering costs:

Overview of the NLPCC 2026 Shared Task 11: Agent-Based Experiment Reproduction from Scientific Papers

arXiv:2609.11117v1 Announce Type: new Abstract: Reproducibility is essential to scientific progress, yet the growing volume and complexity of scientific publications make exhaustive manual verificatio

ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediation

arXiv:2609.11101v1 Announce Type: new Abstract: Dispute mediation is essential for maintaining social harmony and resilience, yet developing skilled mediators is costly and time-consuming. Existing LL