Search: “context”

Locality Matters for Training-Free Audio Token Compression in Audio-Language Models

arXiv:2605.25179v1 Announce Type: new Abstract: Audio-language models (ALMs) are increasingly used for audio captioning, question answering, and open-ended audio understanding, but their inference cos

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Research

Machine Intelligence that Understands Visual and Linguistic Information and Interacts with Humans and Environments

DGX agent

arXiv:2605.24020v1 Announce Type: cross Abstract: Advancements at the intersection of computer vision and natural language processing are crucial for applications like assistive tech, multimedia query

researcharxiv-cs-ai

26 May 2026

Memory-Induced Tool-Drift in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

Neural Router: Semantic Content Matching for Agentic AI

arXiv:2605.25701v1 Announce Type: cross Abstract: Large language models (LLMs) can serve as the semantic-matching engine of a content-based publish/subscribe broker for agentic AI across the edge-clou

PathMem: Toward Cognition-Aligned Memory Transformation for Pathology MLLMs

arXiv:2603.09943v2 Announce Type: replace Abstract: Computational pathology demands both visual pattern recognition and dynamic integration of structured domain knowledge, including taxonomy, grading

researcharxiv-cs-ai

Re-defining Humor Data Objects for AI Humor Research

arXiv:2605.25171v1 Announce Type: new Abstract: In most existing AI humor research, humor was treated as either 'present' or 'not present.' We explore the concept of humor as a social interaction with

researcharxiv-cs-cl

SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning

arXiv:2509.05614v3 Announce Type: replace-cross Abstract: Pruning is a typical acceleration technique for compute-bound models by removing computation on unimportant values. Recently, it has been appl

local-aiarxiv-cs-ai

The Age of Curiosity Meets the Age of AI: Benchmarking Child Safety in Large Language Models

arXiv:2605.25510v1 Announce Type: new Abstract: Children increasingly have access to Large Language Models (LLMs), which may expose them to responses that are developmentally inappropriate or require

The Model Parking Tax: Quantifying the Hidden Energy Cost of Always-On GPU Model Deployment

arXiv:2605.23918v1 Announce Type: cross Abstract: The AI inference industry keeps models loaded in GPU memory around the clock to avoid cold-start latency, implicitly treating idle power as a fixed co

local-aiarxiv-cs-lg

They Are Not the Same: Direct Causes Are Not Grounded Emotion Explanations

arXiv:2605.25208v1 Announce Type: new Abstract: Emotion-Cause Pair Extraction (ECPE) was introduced to explain why an emotion occurs, but this goal is now often reduced to binary pair/non-pair predict

researcharxiv-cs-cl

Transformer-based few-shot learning for modeling Electricity Consumption Profiles with minimal data across thousands of domains

arXiv:2408.08399v3 Announce Type: replace Abstract: Electricity Consumption Profiles (ECPs) are crucial for operating and planning power distribution systems, especially with the increasing number of

UWM-JEPA: Predictive World Models That Imagine in Belief Space

model-releasesarxiv-cs-ai

arXiv:2605.25313v1 Announce Type: cross Abstract: World models for partially observed environments must imagine multiple compatible hidden futures and steer between them under counterfactual actions.

XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation

arXiv:2510.06672v3 Announce Type: replace Abstract: Reinforcement learning algorithms such as GRPO have driven recent advances in large language model (LLM) reasoning. While scaling the number of roll

safetyarxiv-cs-lg

Building a privacy-preserving Federated Recommender system for mobile devices

arXiv:2605.22924v1 Announce Type: new Abstract: Serving personalized content on mobile devices has traditionally required pooling sensitive user data on centralized servers, a practice increasingly at

local-aiarxiv-cs-lg

Applications

Emotion Recognition in Sign Language Conversation

arXiv:2605.23328v1 Announce Type: new Abstract: Emotion Recognition in Conversation is a core component of affective computing, while current resources of sign language emotion datasets primarily focu

applicationsarxiv-cs-cl

From Residuals to Reasons: LLM-Guided Mechanism Inference from Tabular Data

arXiv:2605.22897v1 Announce Type: new Abstract: A persistent challenge in machine learning for scientific applications is jointly achieving prediction and understanding. Statistical models excel on st

agentsarxiv-cs-lg

General Hazard Detection

arXiv:2605.23304v1 Announce Type: new Abstract: Hazard, as an abstract concept, is typically defined through cognitive-level logical reasoning rather than concrete examples. In contrast, existing haza

safetyarxiv-cs-cv

Is TabPFN the Silver Bullet for Insurance Pricing?

arXiv:2605.22892v1 Announce Type: cross Abstract: Modelling claim frequency and severity for non-life insurance pricing predominantly relies on generalised linear models, with gradient-boosted machine

Applications

Learning Individual Dynamics from Sparse Cross-Sectional Snapshots

arXiv:2605.23470v1 Announce Type: cross Abstract: Predicting how a dynamical unit evolves over time - how an individual ages, an epidemic spreads, or a physical system degrades - typically requires de

applicationsarxiv-cs-ai

LFRAG: Layout-oriented Fine-grained Retrieval-Augmented Generation on Multimodal Document Understanding

model-releasesarxiv-cs-ai

arXiv:2605.22829v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for enhancing Large Language Models (LLMs) with external knowledg

Memorization Dynamics of Fill-in-the-Middle Pretraining

model-releasesarxiv-cs-ai

arXiv:2605.22981v1 Announce Type: cross Abstract: Fill-in-the-middle (FIM) is a pretraining objective widely used to equip causal language models with infilling ability, yet its effect on verbatim mem

ObjectCache: Layerwise Object-Storage Retrieval for KV Cache Reuse

arXiv:2605.22850v1 Announce Type: cross Abstract: Prefix KV caching has become a key mechanism in LLM serving: it reduces time to first token (TTFT) by avoiding redundant computation across requests t

local-aiarxiv-cs-ai

OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations

arXiv:2605.23668v1 Announce Type: cross Abstract: Although large language model (LLM) conversational systems process millions of multi-turn dialogues daily, they remain fundamentally reactive: they re

researcharxiv-cs-ai

RoboSurg-VQA: A Multimodal Benchmark for Surgical Segmentation-Aware Visual Question Answering

model-releasesarxiv-cs-cv

arXiv:2605.23068v1 Announce Type: new Abstract: Reliable visual understanding in robot-assisted and minimally invasive surgery (RMIS/MIS) demands more than accurate masks: in clinical practice, clinic

WeCon: An Efficient Weight-Conditioned Neural Solver for Multi-Objective Combinatorial Optimization Problems

arXiv:2605.22876v1 Announce Type: new Abstract: Existing neural solvers for Multi-Objective Combinatorial Optimization Problems (MOCOPs) commonly adopt decomposition-based strategies that scalarize an

World Machine: Towards Generative World Modeling for Time-Series

arXiv:2605.23025v1 Announce Type: new Abstract: World models represent a paradigm shift in generative AI, pursuing predictive understanding and controllable simulation of environments in a structured

PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting

arXiv:2605.21550v1 Announce Type: new Abstract: Electricity load peak forecasting (ELPF), simultaneously predicting peak timing and intensity, is a prerequisite for effective grid scheduling and risk

23 May 2026

A Comparative Study of Language Models for Khmer Retrieval-Augmented Question Answering

arXiv:2605.22099v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm for grounding large language model (LLM) outputs in retrieved evidence, thereby

AMEL: Accumulated Message Effects on LLM Judgments

arXiv:2605.22714v1 Announce Type: cross Abstract: Large language models are routinely used as automated evaluators: to review code, moderate content, or score outputs, often with many items passing th

Tutorials

Cross-Domain Human Action Recognition from Multiview Motion and Textual Descriptions

arXiv:2605.22697v1 Announce Type: new Abstract: Robustness to domain changes is a key capability for effective deployment of human action recognition systems in real-world scenarios, where action cate

tutorialsarxiv-cs-cv

MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering

arXiv:2605.22269v1 Announce Type: new Abstract: Long streaming video QA remains challenging due to growing visual tokens and limited reasoning length of large language models (LLMs). KV-caching stores

researcharxiv-cs-cv

Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation

arXiv:2605.22487v1 Announce Type: new Abstract: Recent advances in Multilingual Large Language Models (MLLMs) have significantly enhanced cross-lingual conversational capabilities, yet modeling cultur

Scene Abstraction for Lexical Semantics: Structured Representations of Situated Meaning

arXiv:2605.22542v1 Announce Type: new Abstract: Coffee and tea share many properties, yet they evoke strikingly different situations, atmospheres, and affective associations. These situated dimensions

researcharxiv-cs-cl

Video-o3: Native Interleaved Clue Seeking for Long Video Multi-Hop Reasoning

arXiv:2601.23224v2 Announce Type: replace Abstract: Existing multimodal large language models for long-video understanding predominantly rely on uniform sampling and single-turn inference, limiting th

researcharxiv-cs-cv

'Would You Want an AI Tutor?' Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom

arXiv:2503.02885v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following ea

safetyarxiv-cs-cl

X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction

arXiv:2605.05765v2 Announce Type: replace Abstract: Inspired by the development of OpenClaw, there is a growing demand for mobile-based personal agents capable of handling complex and intuitive intera

safetyarxiv-cs-cv

A Mechanistic Study of Tabular Foundation Models

arXiv:2605.21288v1 Announce Type: new Abstract: Tabular foundation models with different architectures converge in accuracy across a range of classification and regression tasks. This raises questions

Bayesian Preference Learning for Test-Time Steerable Reward Models

arXiv:2602.08819v2 Announce Type: replace-cross Abstract: Reward models are central to aligning language models with human preferences via reinforcement learning (RL). As RL is increasingly applied to

safetyarxiv-cs-cl

Control and optimization for Neural Partial Differential Equations in Supervised Learning

arXiv:2506.20764v2 Announce Type: replace-cross Abstract: Although there is a substantial body of literature on control and optimization problems for parabolic and hyperbolic systems, the specific pro

Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models

arXiv:2605.21227v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for writing assistance in small contact languages, yet it is unclear whether they respect community n

GROW: Aligning GRPO with State-Action Modeling for Open-World VLM Agents

arXiv:2605.20246v1 Announce Type: new Abstract: Recently, vision-language model (VLM) agents have shown promising progress in open-world tasks, where successful task completion often requires multiple

safetyarxiv-cs-lg

Instance Discrimination for Link Prediction

arXiv:2605.20257v1 Announce Type: new Abstract: Recently, instance discrimination models have emerged as a major solution for self-supervised learning. Having already demonstrated its effectiveness in

MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing

arXiv:2603.06007v2 Announce Type: replace Abstract: Large language model-based (LLM-based) multi-agent systems (MAS) are increasingly used to extend agentic problem solving via role specialization and

agentsarxiv-cs-cl

Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs

arXiv:2605.20315v1 Announce Type: new Abstract: LLM agents have recently emerged as a powerful paradigm for solving complex tasks through planning, tool use, memory retrieval, and multi-step interacti

agentsarxiv-cs-cl

Mobile UMI: Cross-View Diffusion Policy with Decoupled Kinematics for Mobile Manipulation

arXiv:2605.20894v1 Announce Type: new Abstract: Mobile imitation learning on portable demonstration interfaces faces two coupled bottlenecks: locomotion-contaminated action labels and inference-induce

safetyarxiv-cs-ro

ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning

arXiv:2605.20342v1 Announce Type: new Abstract: Training large multimodal models (LMMs) via reinforcement learning (RL) to natively invoke video-processing tools (e.g., cropping) has become a promisin

agentsarxiv-cs-cv

Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators

model-releasesarxiv-cs-lg

arXiv:2605.20978v1 Announce Type: new Abstract: Graph Network Simulators (GNSs) have emerged as powerful surrogates for complex physics-based simulation, offering inherent differentiability and orders

Agentic Trading: When LLM Agents Meet Financial Markets