Search: “models”

EpiEvolve: Self-Evolving Agents for Streaming Pandemic Forecasting under Regime Shifts

arXiv:2606.05513v1 Announce Type: cross Abstract: Epidemic LLM forecasters are usually trained and evaluated as static supervised models, whereas operational pandemic forecasting is a streaming proces

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Research

ExpSpeech-Net: Multimodal Fusion of Expression and Speech for Deepfake Detection

DGX agent

arXiv:2606.05760v1 Announce Type: new Abstract: Deepfake videos are increasingly challenging the credibility of online content. Many existing detection methodology relies on complex, resource-intensiv

researcharxiv-cs-cv

5 Jun 2026

Flow-based Policy Adaptation without Policy Updates

arXiv:2606.06461v1 Announce Type: new Abstract: Leveraging prior knowledge from pretrained policies, foundation models, or human operators offers an efficient alternative to learning robot skills from

safetyarxiv-cs-ro

Harnessing Generalist Agents for Contextualized Time Series

arXiv:2606.05404v1 Announce Type: cross Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, real-world practitioners often require end-to-end

HomeWorld: A Unified Floorplan-to-Furnished Framework for Generating Controllable, Densely Interactive Whole-Home Scenes

arXiv:2606.06390v1 Announce Type: new Abstract: Indoor scene generation is crucial for robot simulation and modern interior design. However, complex layouts together with scarce 3D scene data make lea

HyperVis: Continuous Latent Visual Relational Graphs on the Lorentz Hyperboloid for Compositional Reasoning

arXiv:2606.06100v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle with compositional reasoning that requires understanding inter-object relationships. A natural remedy is to injec

Imagine Before You Predict: Interleaved Latent Visual Reasoning for Video Event Prediction

arXiv:2606.05769v1 Announce Type: new Abstract: Video event prediction (VEP) requires models to infer unobserved future states from partial video evidence. Existing video MLLMs usually verbalize inter

In-Context Multiple Instance Learning

arXiv:2606.06458v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied

applicationsarxiv-cs-cv

Learning Predictive Visuomotor Coordination

arXiv:2503.23300v2 Announce Type: replace Abstract: Understanding and predicting human visuomotor coordination is crucial for applications in robotics, human-computer interaction, and assistive techno

applicationsarxiv-cs-cv

MemoryCard: Topic-Aware Multi-Modal Clue Compression for Long-Video Question Answering

arXiv:2606.05917v1 Announce Type: cross Abstract: Long-video question answering remains challenging for Vision-Language Models (VLMs), as answer-relevant evidence is often sparse, transient, and tempo

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

arXiv:2606.06473v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE),

Next-Generation Parallel Decoder for LPDR: Architectural Optimization and Class-Balanced GAN-Augmentation

arXiv:2606.05785v1 Announce Type: new Abstract: Real-Time License Plate Detection and Recognition (LPDR) forms the backbone of modern smart cities. Although the YOLOV5-PDLPR model substantially improv

NIV: Neural Axis Variations for Variable Font Generation

arXiv:2606.05261v1 Announce Type: new Abstract: Variable fonts enable continuous variation of glyph geometry along semantic design axes such as weight, width, slant, and optical size. However, constru

On Advantage Estimates for Max@K Policy Gradients

arXiv:2606.06080v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is widely used for post-training reasoning models, but sparse outcome rewards make exploration difficul

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs

arXiv:2606.05858v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened new avenues for generating training-free text embeddings. However, the causal attention in d

Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions

arXiv:2606.06443v1 Announce Type: new Abstract: Large language models are increasingly used to simulate social media users and infer how individuals may respond to online discussions. However, it rema

RoCA: Robust Cross-Domain End-to-End Autonomous Driving

arXiv:2506.10145v3 Announce Type: replace Abstract: End-to-end (E2E) autonomous driving has recently emerged as a new paradigm, offering significant potential. However, few studies have looked into th

agentsarxiv-cs-cv

Tutorials

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning

arXiv:2606.06041v1 Announce Type: new Abstract: As robotic systems become more sophisticated, the growing complexity of their motion planning models and the longer training times pose substantial chal

tutorialsarxiv-cs-ro

Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars

arXiv:2606.05912v1 Announce Type: new Abstract: Modeling dynamic facial expressions using 3D Gaussian representations remains challenging due to their unstructured nature. Conventional Gaussian avatar

Staying with the Uncertainty: Uncertainty-Scaffolding Strategies for Artificial Moral Advisors in LLM-to-LLM Simulated Conversations

arXiv:2606.05890v1 Announce Type: new Abstract: LLMs are increasingly deployed as Artificial Moral Advisors (AMA) in a variety of contexts: what kind of conversational patterns should they display? In

Toward Culturally Aligned LLMs through Ontology-Guided Multi-Agent Reasoning

arXiv:2601.21700v3 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly support culturally sensitive decision making, yet often exhibit misalignment due to skewed pretraining dat

Towards Label-Noise Resistant Learning via Optimal Brain Damage Masking

arXiv:2508.09697v3 Announce Type: replace-cross Abstract: Noisy labels are inevitable in real-world scenarios. Due to the strong capacity of deep neural networks to memorize corrupted labels, these no

applicationsarxiv-cs-cv

Two-Way Is Better Than One: Bidirectional Alignment with Cycle Consistency for Exemplar-Free Class-Incremental Learning

arXiv:2606.05675v1 Announce Type: cross Abstract: Continual learning (CL) seeks models that acquire new skills without erasing prior knowledge. In exemplar-free class-incremental learning (EFCIL), thi

safetyarxiv-cs-cv

What's in a Name? Morphological Shortcuts by LLMs in Pharmacology

arXiv:2606.05616v1 Announce Type: new Abstract: The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

arXiv:2606.05626v1 Announce Type: new Abstract: Machine-generated text (MGT) attribution aims to identify the specific generator responsible for a given text, thereby providing fine-grained evidence f

ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation

arXiv:2606.04189v1 Announce Type: new Abstract: Aspect-Based Sentiment Analysis (ABSA) requires high-quality datasets to train reliable models. However, existing annotation tools treat output as flat

BEATS: Bootstrapping E-commerce Attribute Taxonomies for Search through Iterative Human-AI Collaboration

arXiv:2606.04909v1 Announce Type: cross Abstract: E-commerce platforms in emerging markets often operate with underdeveloped product catalogs that contain only category taxonomies but lack structured

applicationsarxiv-cs-cl

Hardware

Cartridges at Scale: Training Modular KV Caches over Large Document Collections

arXiv:2606.04557v1 Announce Type: new Abstract: Large Language Models can reason over long contexts, yet prefilling millions of tokens is wasteful as much of the content remains static across queries.

hardwarearxiv-cs-cl

CleanCodec: Efficient and Robust Speech Tokenization via Perceptually Guided Encoding

arXiv:2606.04418v1 Announce Type: cross Abstract: Neural audio codecs are a key component of speech processing pipelines, compressing audio into discrete tokens for downstream modeling. However, exist

Constrained Adaptive Rejection Sampling

arXiv:2510.01902v2 Announce Type: replace Abstract: Language Models (LMs) are increasingly used in applications where generated outputs must satisfy strict semantic or syntactic constraints. Existing

Continuum Robot State Estimation with Actuation Uncertainty

arXiv:2601.04493v3 Announce Type: replace Abstract: Continuum robots are flexible, slender manipulators well suited for confined surgical environments. In these settings, unknown interaction forces an

researcharxiv-cs-ro

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts

arXiv:2606.04661v1 Announce Type: new Abstract: Prompts tuned for accuracy often grow long, raising inference cost on every model call. The best accuracy-cost trade-off depends on the task and the bud

DAR: Deontic Reasoning with Agentic Harnesses

arXiv:2606.05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liabili

agentsarxiv-cs-ai

Decentralized EM Algorithm for Gaussian Mixtures under Data Heterogeneity and Partial Labeling

arXiv:2411.05591v2 Announce Type: replace-cross Abstract: We systematically study several network-based Expectation-Maximization (EM) algorithms for the Gaussian mixture model within decentralized fed

Drift-Augmented Scoring: Text-Derived Noise Robustness for Zero-Shot Audio-Language Classification

arXiv:2606.04844v1 Announce Type: cross Abstract: Contrastive audio-language models such as CLAP enable zero-shot audio classification: a sound is labelled by matching its embedding to text prompt emb

Hardware

DSA: Dynamic Step Allocation for Fast Autoregressive Video Generation

arXiv:2606.04432v1 Announce Type: new Abstract: Video diffusion transformers have achieved state-of-the-art visual quality, but their high inference cost remains a major bottleneck for real-time appli

hardwarearxiv-cs-cv

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

arXiv:2606.04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes. Computational epitope prediction is critical for unders

EvalStop: Using World Feedback to Detect and Correct Reward Overoptimization in Multi-Tenant RLHF Platforms

arXiv:2606.04145v1 Announce Type: cross Abstract: Cloud LLM fine-tuning platforms increasingly serve RLHF workloads, where a learned reward model is optimized as a proxy for human quality. As Gao et a

Explaining a probabilistic prediction on the simplex with Shapley compositions

arXiv:2408.01382v3 Announce Type: replace Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of e

Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them)

arXiv:2606.05145v1 Announce Type: cross Abstract: When post-trained language models fail on reasoning problems, the common test-time-scaling response is to spend more compute on additional attempts, a

Fast & Faithful Function Vectors

arXiv:2606.05079v1 Announce Type: new Abstract: Function vectors (FVs) are task representations elicited during in-context learning that can be used to steer Large Language Models (LLMs). However, des

Finite-Iteration Local Dynamics and Warm Starts for Alternating Power Iteration in Spiked Tensor PCA

arXiv:2606.04065v1 Announce Type: cross Abstract: We study simultaneous alternating power iteration for fixed-order asymmetric rank-one spiked tensor models. Our main contribution is a finite-iteratio

Local Ai

Identifying Gems from Roman RAPIDly

arXiv:2606.05103v1 Announce Type: cross Abstract: The Nancy Grace Roman Space Telescope (Roman), set for launch as early as September 2026, will conduct wide-field infrared imaging surveys with unprec

local-aiarxiv-cs-cv

In-Context Graphical Inference

arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth

Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning

arXiv:2606.04061v1 Announce Type: new Abstract: Large-scale web-harvested datasets have fueled the progress of cross-modal retrieval but inevitably suffer from noisy correspondence, which severely deg

LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding

arXiv:2606.04302v1 Announce Type: new Abstract: Key-value (KV) caching accelerates inference of large language models (LLMs) by reusing past computations for generated tokens. Its importance becomes e

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers

arXiv:2601.07036v2 Announce Type: replace-cross Abstract: Hybrid reasoning language models are commonly controlled through high-level Think/No-think instructions to regulate reasoning behavior, yet we

Tutorials

Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis

arXiv:2606.04414v1 Announce Type: new Abstract: Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment.

tutorialsarxiv-cs-cv