Search: “context”

FlowNar: Scalable Streaming Narration for Long-Form Videos

arXiv:2606.00620v1 Announce Type: new Abstract: Recent Large Multimodal Models (LMMs), primarily designed for offline settings, are ill-suited for the dynamic requirements of streaming video. While re

researcharxiv-cs-cv

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ForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation

DGX agent

arXiv:2606.01549v1 Announce Type: new Abstract: AI-based semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the comp

local-aiarxiv-cs-cv

2 Jun 2026

From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection

arXiv:2602.03018v2 Announce Type: replace Abstract: Outlier detection (OD) is widely used in practice; but its effective deployment on new tasks is hindered by lack of labeled outliers, which makes al

GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing

arXiv:2606.00860v1 Announce Type: cross Abstract: Self-report questionnaires remain the prevailing tool for probing the psychological states of persona-conditioned agents (PC-Agents). However, classic

'I've Seen How This Goes': Characterizing Diversity via Progressive Conditional Surprise

arXiv:2606.01811v1 Announce Type: cross Abstract: Measuring the diversity of creative outputs is central to evaluating post-training mode collapse, comparing decoding strategies, and quantifying creat

Jailbreaking Multimodal Large Language Models using Multi-Clip Video

arXiv:2606.02111v1 Announce Type: cross Abstract: As multimodal large language models (MLLMs) have advanced to process video inputs, concerns have emerged about their potential for malicious misuse. P

KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation

arXiv:2606.01282v1 Announce Type: new Abstract: Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cu

safetyarxiv-cs-cv

LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition

arXiv:2606.00260v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from ambient sensors enables smart-home applications such as health monitoring and assisted living. In realistic deploy

researcharxiv-cs-cv

LLMs Need Encoders for Semantic IDs Too

arXiv:2606.00324v1 Announce Type: cross Abstract: Multimodal LLMs use dedicated encoders to bridge non-language modalities (vision encoders for images, depth models for audio codec tokens) because raw

tutorialsarxiv-cs-ai

Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture

arXiv:2606.00288v1 Announce Type: new Abstract: Large language models are undergoing a transition from model technology to system technology. As developers use Codex, Claude Code, AutoGPT, and related

Parameter-Efficient Fine-Tuning of Large Pretrained Models for Instance Segmentation Tasks

arXiv:2606.01947v1 Announce Type: cross Abstract: Research and applications in artificial intelligence have recently shifted with the rise of large pretrained models, which deliver state-of-the-art re

RCEM: Embedder Equipped with Query Rewriting Skill for Robust Conversational Search in Distributional Shift

arXiv:2606.01697v1 Announce Type: new Abstract: Conversational search has become increasingly important in retrieval-augmented generation (RAG) systems, where users interact with AI assistants through

tutorialsarxiv-cs-cl

Agents

Recognize Your Orchestrator: An Entropy Dynamics Perspective for LLM Multi-Agent Systems

arXiv:2606.01351v1 Announce Type: new Abstract: The transition from single-turn models to Multi-Agent Systems (MAS) promises enhanced problem-solving capabilities, yet the centralized orchestration to

agentsarxiv-cs-ai

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete

model-releasesarxiv-cs-lg

arXiv:2606.01532v1 Announce Type: new Abstract: Positional encoding (PE) is widely viewed as necessary for transformers to process ordered sequences: without them, the next-token map appears permutati

Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints

arXiv:2604.01841v2 Announce Type: replace Abstract: Clinical prediction from structured electronic health records (EHRs) is challenging due to high dimensionality, heterogeneity, class imbalance, and

SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection

arXiv:2404.11326v5 Announce Type: replace Abstract: In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets

tutorialsarxiv-cs-cv

SHARP: Sleep-based Hierarchical Accelerated Replay for Long Range Non-Stationary Temporal Pattern Recognition

arXiv:2606.00732v1 Announce Type: new Abstract: Learning long-range non-stationary temporal patterns remains a core challenge for modern sequence models, particularly in strict streaming settings. In

SkillPager: Query-Adaptive Intra-Skill Navigation via Semantic Node Retrieval

arXiv:2606.00822v1 Announce Type: cross Abstract: Skill-based LLM agents increasingly rely on long procedural documents, but full-document prompting wastes tokens and dilutes information critical to e

Subliminal Learning is a LoRA Artifact

arXiv:2606.00831v1 Announce Type: new Abstract: Subliminal learning is a phenomenon where language models can transmit behavioral traits to other models through seemingly innocuous data (Cloud et al.,

TCAR-Gen: Temporal Graph Retrieval with Evidence Fusion for Knowledge-Grounded Generation

arXiv:2606.00029v1 Announce Type: cross Abstract: Retrieval-augmented generation systems struggle with temporal reasoning and evidence fusion when answering complex questions over historical criminal

THRD: A Training-Free Multi-Turn Defense Framework for Jailbreak Attacks on Large Language Models

arXiv:2606.01738v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks pose a growing threat to LLMs by exploiting conversational dynamics such as gradual escalation and cross-turn coordinatio

ToolSelf: Unifying Task Execution and Self-Reconfiguration via Tool-Driven Emergent Adaptation

arXiv:2602.07883v3 Announce Type: replace Abstract: LLM-powered agentic systems excel at complex long-horizon tasks, but remain constrained by static configurations fixed before execution. Such rigidi

Towards a Physics Foundation Model

arXiv:2509.13805v4 Announce Type: replace-cross Abstract: Foundation models have revolutionized natural language processing through a ``train once, deploy anywhere'' paradigm, where a single pre-train

tutorialsarxiv-cs-ai

TRACE: Trajectory Risk-Aware Compression for Long-Horizon Agent Safety

arXiv:2606.00611v1 Announce Type: new Abstract: Long-horizon LLM agents produce safety evidence across long trajectories, where sparse, delayed, and compositional risk signals often escape local moder

When Jokes Cross the Line: Analyzing Regular Humor and Dark Humor in YouTube Shorts

arXiv:2606.00046v1 Announce Type: cross Abstract: Video platforms such as YouTube have reshaped how users engage with entertainment and information, emphasizing brief, highly engaging content such as

When Tabular Foundation Models Transfer Across Modalities: A Systematic Evaluation Across 95 Datasets, 7 Modalities, and Two Regimes

arXiv:2606.02106v1 Announce Type: new Abstract: We present a single classification pipeline that combines an Equiangular Tight Frame (ETF) preprocessing stage with a tabular foundation model for in-co

tutorialsarxiv-cs-lg

Chem-PerturBridge: a harmonized compendium of small molecule perturbation transcriptomic effects

arXiv:2605.31522v1 Announce Type: new Abstract: Large perturbation models require training data encompassing chemical, cellular, and assay diversity. Current transcriptomic resources for small-molecul

DRIFT: Joint Channel Estimation and Prediction Towards Pilotless 6G Non-Terrestrial Networks

arXiv:2605.31065v1 Announce Type: cross Abstract: Non-terrestrial networks (NTNs) are expected to play a pivotal role in sixth-generation (6G) systems by enabling ubiquitous connectivity and massive c

researcharxiv-cs-ai

Extending AI for Research to the Humanities: A Multi-Agent Framework for Evidence-Grounded Scholarship

model-releasesarxiv-cs-cl

arXiv:2605.30947v1 Announce Type: new Abstract: LLM-based research agents have advanced rapidly in science and engineering, where research is organized around executable experiments, code, and quantit

GUI-C^2: Coarse-to-Fine GUI Grounding via Difficulty-Aware Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2605.30884v1 Announce Type: new Abstract: Existing agentic reinforcement learning methods for GUI grounding have limitations at two levels. At the data level, current approaches typically treat

ImmersiveTTS: Environment-Aware Text-to-Speech with Multimodal Diffusion Transformer and Domain-Specific Representation Alignment

arXiv:2605.30965v1 Announce Type: cross Abstract: Recent advancements in text-guided audio generation have yielded promising results in diverse domains, including sound effects, speech, and music. How

Improving Selective Classification with Pairwise Queries for Binary Classification

arXiv:2605.30615v1 Announce Type: new Abstract: In selective classification, a model predicts the labels of data samples where it is confident, and abstains from predicting labels for samples on which

Learning Whom to Trust: Market-Feedback Adaptive Retrieval for Frozen LLMs in Event-Driven Financial RAG

model-releasesarxiv-cs-cl

arXiv:2605.31201v1 Announce Type: new Abstract: Financial retrieval-augmented generation (RAG) systems typically rank evidence by textual relevance, but in financial markets the useful evidence source

Agents

LH-Bench: Skill-Grounded Evaluation of Long-Horizon Agents on Subjective Enterprise Tasks

arXiv:2603.22744v2 Announce Type: replace Abstract: Large language models excel on objectively verifiable tasks such as math and programming, where evaluation reduces to unit tests or a single correct

agentsarxiv-cs-ai

Neuro-symbolic Syntactic Parsing: Shaping a Neural Network with the CYK Algorithm

arXiv:2605.31421v1 Announce Type: cross Abstract: In this paper, we show the possibility of a direct injection of algorithms into neural network architecture. We focus on a complex algorithm, that is,

Local Ai

Reasoning-Aware Multimodal Fusion for Hateful Video Detection

arXiv:2512.02743v2 Announce Type: replace-cross Abstract: Hate speech in online videos is posing an increasingly serious threat to digital platforms, especially as video content becomes increasingly m

local-aiarxiv-cs-ai

SpongeBob: Sync-Aware Harmonious Audio-Visual Generative Editing

arXiv:2605.25193v2 Announce Type: replace Abstract: Visual and acoustic events in the physical world are inherently coupled, yet existing video editing methods typically adopt decoupled pipelines, lac

safetyarxiv-cs-cv

Stateful Online Monitoring Catches Distributed Agent Attacks

arXiv:2605.31593v1 Announce Type: cross Abstract: Language models can find thousands of severe software vulnerabilities, and agents are increasingly being misused for cyberattacks. To avoid detection,

Universal Decision Learners

arXiv:2605.30694v1 Announce Type: new Abstract: Many theories of decision making -- planning, reinforcement learning, causal intervention, online learning, and game-theoretic equilibrium -- turn local

Applications

VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning

arXiv:2605.31457v1 Announce Type: new Abstract: With the rapid advancement of large multimodal models (LMMs), inference-time overhead has become a key bottleneck for real-world deployment. Existing me

applicationsarxiv-cs-cv

Local Ai

When English Rewrites Local Knowledge: Global Narrative Dominance in Large Language Models

arXiv:2605.30481v1 Announce Type: new Abstract: Large language models (LLMs) are widely used as cross-lingual knowledge interfaces. However, culturally grounded questions often reflect globally domina

local-aiarxiv-cs-cl

A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning

model-releasesarxiv-cs-lg

arXiv:2605.29454v1 Announce Type: new Abstract: While Membership Inference Attacks (MIAs) are the prevailing method for identifying training data, their application has expanded into privacy auditing

A Predictive Law for On-Policy Self-Distillation From World Feedback

arXiv:2605.30070v1 Announce Type: cross Abstract: Moving beyond simple scalar rewards toward richer world feedback is a natural path to more scalable RL post-training. On-policy self-distillation (OPS

Adaptive Interviewing for Persona Simulation in LLMs: Evidence-Grounded Reasoning Improves Decision Alignment

arXiv:2605.29458v1 Announce Type: cross Abstract: Accurately simulating the decisions of a specific individual remains challenging for large language models (LLMs), partly because persona information

AIRGuard: Guarding Agent Actions with Runtime Authority Control

arXiv:2605.28914v1 Announce Type: cross Abstract: Tool-using language agents turn model decisions into external side effects: they read files, run scripts, call APIs, send messages, and invoke Model C

BenchTrace: A Benchmark for Testing Reflection Ability and Controlled Evolution in LLM Agents

arXiv:2605.29225v1 Announce Type: new Abstract: Self-evolving agents improve over time by reflecting on past failures, but existing evaluation is limited in two ways: it measures only task scores, lea

GRUFF: LLM Pronoun Fidelity, Reasoning, and Biases in German

arXiv:2605.30214v1 Announce Type: new Abstract: Third-person singular pronouns have long been used to study stereotypical biases in language models and to test their abilities to reason about referenc

safetyarxiv-cs-cl

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models

arXiv:2605.28828v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve impressive performance across many tasks but remain prone to hallucination, especially in long-form generation wh

researcharxiv-cs-ai