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Open-UniMo: Towards Unified Motion-Language Understanding and Generation in the Open World

arXiv:2609.14615v1 Announce Type: cross Abstract: Unified motion generation and understanding is crucial for embodied AI systems that can both synthesize and interpret human actions in open-world envi

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Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data

DGX agent

arXiv:2609.13940v1 Announce Type: new Abstract: Effective anomaly detection frameworks are a central pillar of the Industry 4.0 paradigm. In this paper, we introduce an Optimal Transport (OT)-based fr

model-releasesarxiv-cs-lg

15 Sept 2026

Overflip: Repetition-Induced Label Flips in Guardrail Models

arXiv:2609.15013v1 Announce Type: new Abstract: Guardrail models are classifiers deployed to screen malicious prompts and responses in LLM-based services. To meet latency constraints, many lightweight

PACE: Progressive Angular-to-Norm Contrastive Embedding

arXiv:2609.15152v1 Announce Type: cross Abstract: Multimodal embedding models encode heterogeneous inputs into a shared embedding space, enabling efficient similarity computation across modalities and

Parameter-Efficient Adaptation of Pretrained Language Models for Time-Series Forecasting

arXiv:2609.15344v1 Announce Type: new Abstract: We study the adaptation of pretrained language models to univariate time-series forecasting through a parameter-efficient transfer learning framework, w

Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT

arXiv:2609.14106v1 Announce Type: new Abstract: We evaluated parameter-efficient fine-tuning (PEFT) of the Segment Anything Model (SAM) for liver tumor segmentation in abdominal CT of colorectal liver

Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement

arXiv:2609.14529v1 Announce Type: cross Abstract: Rigorous empirical validation of quantum machine learning on natural language tasks remains scarce. We evaluate a 10-qubit hybrid quantum-classical va

Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder

arXiv:2609.14277v1 Announce Type: cross Abstract: Ringdown gravitational waves from binary black hole mergers can be modeled as superpositions of quasinormal modes (QNMs), whose frequencies and excita

Parameter isolation with domain-specific experts for incremental audio classification

arXiv:2609.14730v1 Announce Type: cross Abstract: To successfully deploy a model in time-varying environments such as streaming data prediction and sensing control, domain-incremental learning (DIL) h

PARSE: Provenance-Aware Retrieval Sanitization for Professional Domain LLM Agents

arXiv:2606.17467v3 Announce Type: replace-cross Abstract: Prompt injection defenses evaluated on synthetic benchmarks do not generalize to real enterprise documents, which are longer, denser, and inte

Patient-Level, Leakage-Aware Deep Learning for Cross-Center Periapical Radiograph Classification

arXiv:2609.14703v1 Announce Type: new Abstract: Dental caries and endodontic disease are among the most common health conditions worldwide, and intraoral periapical radiographs are central to their de

Pedestrian Crossing Intent Classification From Event-Based Vision Using Convolutional Spiking Neural Networks With Temporal Augmentation

arXiv:2609.13328v1 Announce Type: cross Abstract: Anticipating whether a pedestrian will cross the road is safety-critical for autonomous vehicles, requiring real-time inference under challenging cond

Per-Matrix Optimality Is Not Enough: Three-Level Optimization for Low-Rank LLM Compression

arXiv:2609.15838v1 Announce Type: cross Abstract: Per-matrix singular value decomposition (SVD) truncation is Eckart-Young optimal in the whitened Frobenius norm, but errors from independently compres

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

arXiv:2609.14973v1 Announce Type: new Abstract: We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the ph

Physically Partitioned KVCache Format for CPU--GPU Load Balancing in MoE Inference

arXiv:2609.14507v1 Announce Type: cross Abstract: Single-GPU long-context inference with Mixture-of-Experts (MoE) models requires spilling the key-value cache (KVCache) to CPU memory. The spilled KV s

PhysMent: An Interactive Approach For LLM Reasoning In Physics Problems

arXiv:2609.13152v1 Announce Type: new Abstract: Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experime

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

arXiv:2609.15029v1 Announce Type: cross Abstract: Backdoor poisoning attacks add poisoned examples to otherwise-clean finetuning data, pairing a trigger with a target behavior that the model learns to

PIDS-Bench: Evaluating Prompt-Injection Detectors Under Over-Defense, Obfuscation, and Distribution Shift

arXiv:2609.15017v1 Announce Type: cross Abstract: Prompt-injection detectors are typically evaluated using aggregate F1 on in-distribution test data, which offers limited insight into behavior under d

PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection

arXiv:2609.15562v1 Announce Type: cross Abstract: As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploit

Planning or Learning: Reliability and Cost in Multi-Asset Maintenance

arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational co

POLARIS: Training-Free Audio Fingerprinting with Saliency-Based Landmarks and Delaunay Grouping

arXiv:2609.14820v1 Announce Type: cross Abstract: This work presents POLARIS, a training-free audio fingerprinting system that selects landmarks from a locally normalized saliency field and groups the

Policy Loopholes in Agent Evaluation: When Policy Ambiguity Masquerades as Agent Error

arXiv:2609.14400v1 Announce Type: new Abstract: Agent benchmarks evaluate policy compliance but assume each policy determines a unique correct action. Natural-language policies can violate this assump

Positioning manuscripts in the scientific landscape with agentic AI

arXiv:2609.13760v1 Announce Type: new Abstract: Publishing a research manuscript is a routine yet demanding part of scientific life: time-consuming, stressful, and often uncertain in outcome. Recent a

Post-Reasoning: Improving the Performance of Non-Thinking Models at No Cost

arXiv:2605.06165v2 Announce Type: replace Abstract: As the widespread adoption of Large Language Models (LLMs) accelerates, token consumption from intermediate reasoning traces increasingly contribute

Pre-PEFT Probing: Weight Statistics and Perturbation Robustness for Layer Selection in VLM Vision Encoders

arXiv:2609.15229v1 Announce Type: cross Abstract: We propose a pre-fine-tuning probing method for Parameter-Efficient Fine-Tuning (PEFT) layer selection, aiming to obtain more stable and higher gains

Pretraining for Sample-Efficient Neural Interfaces

arXiv:2609.13507v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) decode neural activity to restore lost function. Typically, training a high-performance neural decoder requires a large

PRISM-UDE: Physics-Regularized Iterative Symbolic Modeling of 3nm FinFETs via Universal Differential Equation

arXiv:2609.13200v1 Announce Type: cross Abstract: Compact transistor models are the mathematical backbone of circuit simulation. However, at advanced nodes such as 3nm, transport physics becomes too c

Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation

arXiv:2609.15885v1 Announce Type: cross Abstract: This study proposes a privacy-enhanced federated learning framework to address secure collaborative training in distributed data environments. The fra

Programs as Singularities

arXiv:2504.08075v2 Announce Type: replace-cross Abstract: We develop a correspondence between the structure of Turing machines and the structure of singularities of real analytic functions, based on c

Projection-Free Multi-level Algorithms for Stochastic Constrained Compositional Optimization

arXiv:2609.15679v1 Announce Type: cross Abstract: This paper studies projection-free algorithms for stochastic constrained multi-level compositional optimization. In this context, the objective functi

Proportional-Fair Resource Allocation and Dual-Threshold Early-Exit Inference for Secure Cooperative Multi-Layer Edge Intelligence

arXiv:2609.15847v1 Announce Type: cross Abstract: This paper proposes FREDI (Fair Resource Allocation for Edge Dual-Threshold Inference), a secure wireless edge-intelligence framework for event-trigge

PU classification under Non-SCAR: clustering-assisted logistic model with oversampling enhancement

arXiv:2609.14675v1 Announce Type: cross Abstract: This study addresses the PU classification problem under violations of the SCAR assumption. We investigate logistic regression-based approaches, namel

Pull: Lazy Materialization of Working Memory for Stateful LLM Conversations

arXiv:2609.14773v1 Announce Type: new Abstract: As LLM conversations grow to hundreds of turns, full-context injection incurs O(N^2) cumulative token costs, while lossy summarization or hard truncatio

PuzzleMate: Benchmarking MLLMs for Egocentric Puzzle Assistance

arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a

QSTAR: Quantum Selective Transfer with Adaptive Routing

arXiv:2607.21411v1 Announce Type: cross Abstract: Quantum transfer learning (QTL) is often evaluated by replacing a classical classifier with a fixed variational quantum head, but this hides a key que

Quantum-Gated LiteSSD: A Parameter-Efficient Lightweight Hybrid Quantum-Classical Framework for Forward-Looking Sonar Object Detection

arXiv:2609.14025v1 Announce Type: new Abstract: Forward-looking sonar object detection is essential for underwater perception, yet deployment on embedded platforms requires highly compact models. To a

Query-Conditioned Spherical Centroid Aggregation for Multimodal Retrieval

arXiv:2609.15335v1 Announce Type: new Abstract: Multimodal retrieval integrates video, audio, subtitles, and text; however, recent geometric aggregators, such as Gramian volumes, hyperbolic volumes, a

Query-Oblivious Coresets for Softmax Attention: Improved Bounds and Efficient Constructions

arXiv:2609.06327v2 Announce Type: replace-cross Abstract: A query-oblivious coreset for a softmax-attention head is a subset of the key-value pairs whose attention output is within arepsilon of the fu

Question's Gambit: The First Move Matters in Agentic Deep Search

arXiv:2609.14412v1 Announce Type: new Abstract: Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmark

Realtime-Venus: A full-duplex interaction system with asynchronous delegation

arXiv:2609.13814v1 Announce Type: new Abstract: Natural interaction in digital and physical environments requires continuous perception and timely responses. Spoken dialogue relies on acoustic and lin

Reconstructing Is Not Acting: Action-Centric Latent Dynamics Modeling

arXiv:2609.15189v1 Announce Type: new Abstract: Latent action models (LAMs) learn action representations from unlabeled videos by inferring latent actions from visual transitions and reconstructing fu

Refusal Reads Only a Slice of What the Model Knows: Harm-Keyed Routing and Its Exceptions Across Model Families

arXiv:2609.14759v1 Announce Type: cross Abstract: Alignment applied after pretraining is shallow in a measurable way: a single direction in a model's residual stream can be edited out, and the model s

RESKILL: Explicit Failure Attribution and Structured Repair for Interactive Language Agents

arXiv:2609.15684v1 Announce Type: new Abstract: Language agents increasingly rely on reusable skills, but post-failure repair is often handled by opaque one-shot reflection: a model generates a skill

Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels

arXiv:2609.13798v1 Announce Type: cross Abstract: Operator learning is formulated on function spaces, but training data are typically available only through finite-dimensional representations. In enco

Rethinking Camouflage Image Generation towards a Training-Free Paradigm

arXiv:2609.14377v1 Announce Type: new Abstract: Camouflage image generation (CIG) aims to synthesize realistic camouflaged images by blending foreground objects into concealment-compatible background

Reverse Spatio-Temporal Disease Progression Modelling

arXiv:2609.14590v1 Announce Type: new Abstract: Deep learning-based spatio-temporal disease progression models commonly overlook the incubation period of progressive diseases, limiting the use of thos

Rolling Day-Wise Mortality Prediction in Critically Ill Patients With AKI on CRRT Utilizing Machine Pressure Waveforms

arXiv:2609.13524v1 Announce Type: cross Abstract: Critically ill patients with acute kidney injury (AKI) on continuous renal replacement therapy (CRRT) face high mortality, yet current risk assessment

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

arXiv:2609.13463v1 Announce Type: new Abstract: The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reli