Search: “models”

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

arXiv:2605.18587v1 Announce Type: cross Abstract: Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin

Parallel Recursive LSTM

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DGX agent

arXiv:2605.17108v1 Announce Type: new Abstract: Transformers have become the dominant architecture for sequence modeling by using self-attention to enable expressive and highly parallel processing. Ho

researcharxiv-cs-lg

19 May 2026

Prefix-Adaptive Block Diffusion for Efficient Document Recognition

arXiv:2605.16861v1 Announce Type: cross Abstract: Block Diffusion Models (BDMs) support parallel generation, flexible-length output, and KV caching, making them promising for efficient document parsin

researcharxiv-cs-ai

Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation

arXiv:2605.17034v1 Announce Type: cross Abstract: Standard PII filters often miss contextual data leakage in RAG systems, such as non-regulated attribute clusters that collectively identify individual

Privacy Preserving Reinforcement Learning with One-Sided Feedback

arXiv:2605.18246v1 Announce Type: cross Abstract: We study reinforcement learning (RL) in multi-dimensional continuous state and action spaces with one-sided feedback, where the agent receives partial

Probing SMEFT Operators through tar{t}tar{t} Production with Hyper-Graph Neural Networks at the LHC

arXiv:2605.18382v1 Announce Type: cross Abstract: We present a phenomenological study of tar{t}tar{t} production in proton-proton collisions at sqrt{s} = 13~TeV, using a Hyper-Graph Neural Network (H-

Applications

QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction

arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake signals. While classical deep learning models such

applicationsarxiv-cs-lg

Radial-Angular Geometry for Reliable Update Diagnosis in Noisy-Label Learning

arXiv:2605.17429v1 Announce Type: cross Abstract: Noisy-label methods often estimate sample reliability from forward-space signals such as loss, confidence, or entropy. These signals indicate whether

Ranking-Aware Calibration for Reliable Multimodal Reinforcement Learning

arXiv:2605.16999v1 Announce Type: new Abstract: Reinforcement learning post-training has substantially improved the reasoning accuracy of vision-language models, yet the resulting policies remain poor

safetyarxiv-cs-lg

ReBaR: Reference-Based Reasoning for Robust Pose Estimation from Monocular Images

arXiv:2303.11675v3 Announce Type: replace Abstract: R}easoning for Robust Human Pose and Shape Estimation), designed to estimate human body shape and pose from single-view images. ReBaR effectively ad

REC-RL: Referring expression counting via Gaussian and range-based reward optimization

arXiv:2605.16460v1 Announce Type: new Abstract: Referring expression counting (REC) is an intention-driven task that requires context-aware visual reasoning. While recent vision-language models incorp

Reducing Credit Assignment Variance via Counterfactual Reasoning Paths

arXiv:2605.16302v1 Announce Type: cross Abstract: Reinforcement learning for multi-step reasoning with large language models (LLMs) often relies on sparse terminal rewards, leading to poor credit assi

Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Management

arXiv:2605.17036v1 Announce Type: new Abstract: This paper studies autonomous generative AI agents in multi-echelon supply chains using the MIT Beer Game. We identify four inference-time levers that s

Residual Semantic Decomposition of Word Embeddings

model-releasesarxiv-cs-cl

arXiv:2605.17482v1 Announce Type: new Abstract: We introduce Residual Semantic Decomposition (RSD), a neural additive decomposition of word embeddings that balances embedding reconstruction with relat

Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling

arXiv:2605.18599v1 Announce Type: new Abstract: Transformer-based models have advanced feedforward novel view synthesis (NVS). Current architectures such as GS-LRM and LVSM mix semantic information (e

Responsible Agentic AI Requires Explicit Provenance

arXiv:2605.17169v1 Announce Type: new Abstract: Agentic AI is rapidly proliferating across diverse real-world domains such as software engineering, yet public trust has not kept pace. The central reas

ReTAMamba: Reliability-Aware Temporal Aggregation with Mamba for Irregular Clinical Time Series Prediction

arXiv:2605.16380v1 Announce Type: cross Abstract: Clinical time-series data are difficult to model with methods designed for regular sequences because they exhibit irregular sampling, frequent missing

researcharxiv-cs-ai

Roll Out and Roll Back: Diffusion LLMs are Their Own Efficiency Teachers

arXiv:2605.16941v1 Announce Type: new Abstract: Diffusion Large Language Models (DLLMs) promise fast parallel generation, yet open-source DLLMs still face a severe quality-speed trade-off: acceleratin

researcharxiv-cs-cl

RTI-Bench: A Structured Dataset for Indian Right-to-Information Decision Analysis

model-releasesarxiv-cs-cl

arXiv:2605.16843v1 Announce Type: new Abstract: India's Right to Information Act, 2005 gives every citizen the right to demand information from public authorities, yet in practice most people cannot m

SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation

arXiv:2605.16628v1 Announce Type: new Abstract: The SCARED dataset is a widely used benchmark for endoscopic depth estimation, offering ground-truth 3D reconstructions captured with a structured light

Scheduling That Speaks: An Interpretable Programmatic Reinforcement Learning Framework

arXiv:2605.18454v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) has recently emerged as a promising approach to solve combinatorial optimization problems such as job shop schedulin

SE-GA: Memory-Augmented Self-Evolution for GUI Agents

arXiv:2605.16883v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents often struggle with multi-step tasks due to constrained context windows and static policies that fail t

Applications

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling

arXiv:2605.18007v1 Announce Type: new Abstract: Rhetorical Role Labeling (RRL) assigns a functional role to each sentence in a document and is widely used in legal, medical, and scientific domains. Wh

applicationsarxiv-cs-cl

Shallow ReLU^s Networks in L^p-Type and Sobolev Spaces: Approximation and Path-Norm Controlled Generalization

arXiv:2605.18468v1 Announce Type: cross Abstract: We study approximation by shallow ReLU^s networks, sigma_s(t)=max{0,t}^s, and the generalization behavior of such networks under ell_1 path-norm contr

SHED: Style-Homogenized Embedding Alignment for Domain Generalization

arXiv:2605.16973v1 Announce Type: new Abstract: Domain generalization aims to enhance model robustness against unseen domains with embedding distribution shifts. While large-scale vision-language mode

Tutorials

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

arXiv:2512.04746v2 Announce Type: replace-cross Abstract: Extremely low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance de

tutorialsarxiv-cs-ai

SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents

arXiv:2605.18693v1 Announce Type: new Abstract: As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether t

Agents

Speech-Hands: A Self-Reflection Voice Agentic Approach to Speech Recognition and Audio Reasoning with Omni Perception

arXiv:2601.09413v2 Announce Type: replace-cross Abstract: We introduce a voice-agentic framework that learns one critical omni-understanding skill: knowing when to trust itself versus when to consult

agentsarxiv-cs-ai

Spherical VAE with Cluster-Aware Feasible Regions: Guaranteed Prevention of Posterior Collapse

arXiv:2603.10935v4 Announce Type: replace-cross Abstract: Variational autoencoders (VAEs) frequently suffer from posterior collapse, where the latent variables become uninformative as the approximate

Stabilizing Temporal Inference Dynamics for Online Surgical Phase Recognition

arXiv:2605.16387v1 Announce Type: cross Abstract: Online Surgical Phase Recognition (SPR) models can reach high frame-wise accuracy, yet their predictions often lack temporal stability, fragmenting wo

researcharxiv-cs-ai

Stable Routing for Mixture-of-Experts in Class-Incremental Learning

arXiv:2605.17571v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires models to learn new classes sequentially while preserving prior knowledge. Recently, approaches that combine p

Step-wise Rubric Rewards for LLM Reasoning

arXiv:2605.17291v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning in large language models, but rewards only final-answer correc

researcharxiv-cs-lg

StyleText: A Large-Scale Dataset and Benchmark for Stylized Scene Text Inpainting

arXiv:2605.17309v1 Announce Type: cross Abstract: We present StyleText, a large-scale dataset and benchmark for localized scene-text inpainting with style preservation. StyleText contains 28,518 image

SURGE: Approximation-free Training Free Particle Filter for Diffusion Surrogate

arXiv:2605.18745v1 Announce Type: cross Abstract: Diffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve samp

safetyarxiv-cs-lg

Surgical Post-Training: Proximal On-Policy Distillation for Reasoning with Knowledge Retention

arXiv:2603.01683v2 Announce Type: replace-cross Abstract: Injecting new reasoning knowledge into Large Language Models (LLMs) via post-training often induces catastrophic forgetting. Recent studies em

Symphony for Speech-to-Text: Supporting Real-Time Medical Voice Interfaces

arXiv:2605.16545v1 Announce Type: cross Abstract: After decades of use in dictation and, more recently, ambient documentation, speech is emerging as a primary modality for interacting with technology

Taming Audio VAEs via Target-KL Regularization

arXiv:2605.17085v1 Announce Type: cross Abstract: Latent diffusion models have emerged as the dominant paradigm for many generation tasks including audio generation such as text-to-audio, text-to-musi

researcharxiv-cs-lg

Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations

model-releasesarxiv-cs-cl

arXiv:2605.17639v1 Announce Type: new Abstract: Co-citation structure is widely assumed to provide stable retrieval signal in legal information systems. We test this assumption longitudinally by const

The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

The Geometry of Projection Heads: Conditioning, Invariance, and Collapse

arXiv:2605.17180v1 Announce Type: new Abstract: We develop a geometric theory of projection heads in self-supervised learning by modeling the head as a trainable Riemannian metric on the backbone repr

researcharxiv-cs-lg

The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaboration

arXiv:2605.18372v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in educational settings as interactive tools for collaboration. However, their tendency toward syco

Tutorials

The Learnability Gap in Medical Latent Diffusion

arXiv:2605.17087v1 Announce Type: new Abstract: Generative data augmentation with latent diffusion models is a promising strategy for addressing class imbalance in medical imaging, yet current approac

tutorialsarxiv-cs-cv

The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning

arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al

The Powers of Precision: Structure-Informed Detection in Complex Systems -- From Customer Churn to Seizure Onset

arXiv:2601.21170v3 Announce Type: replace Abstract: Emergent phenomena -- onset of epileptic seizures, sudden customer churn, or pandemic outbreaks -- often arise from hidden causal interactions in co

The Symmetries of Three-Layer ReLU Networks

arXiv:2605.18319v1 Announce Type: new Abstract: We develop a framework for analyzing parameter symmetries in deep ReLU networks and obtain a complete characterization of the generic parameter fibers f

Theory of Minimal Weight Perturbations in Deep Networks and its Applications for Low-Rank Activated Backdoor Attacks

arXiv:2601.16880v2 Announce Type: replace Abstract: The minimal norm weight perturbations of DNNs required to achieve a specified change in output are derived and the factors determining its size are

Agents

Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents

arXiv:2504.07347v3 Announce Type: replace-cross Abstract: As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While

agentsarxiv-cs-lg

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval

arXiv:2605.18434v1 Announce Type: cross Abstract: E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This im