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Towards Fast and Effective Long Video Understanding of Multimodal Large Language Models via Adaptive Quasi-Gaussian Sampling

arXiv:2606.24187v1 Announce Type: new Abstract: Long video understanding remains a daunting challenge for Multimodal Large Language Models (MLLMs) due to the excessive computation and memory footprint

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Towards Federated Long-Tailed Graph Learning: An Energy-Guided Dual Decoupling Approach

DGX agent

arXiv:2606.24237v1 Announce Type: new Abstract: Federated Graph Learning facilitates collaborative graph modeling across distributed clients while preserving data privacy. However, real-world data cat

applicationsarxiv-cs-ai

24 Jun 2026

Towards Spec Learning: Inference-Time Alignment from Preference Pairs

arXiv:2606.24004v1 Announce Type: cross Abstract: Steering a large language model (LLM) toward a desired behavior typically relies on an iterative process of hand-crafting a prompt based on a careful

Towards Version-aware Operations and Transaction Memories for Multi-layer MeMo

arXiv:2606.24040v1 Announce Type: cross Abstract: MeMo proposes language models with explicit multi-layer correlation matrix memories (CMMs), where memorization, retrieval, and forgetting are architec

Tractable Reasoning and Conjunctive Query Answering for Defeasible DL-Lite under Rational Closure

arXiv:2606.24279v1 Announce Type: new Abstract: In Description Logics (DLs), reasoning under Rational Closure (RC) is a well-known and widely accepted non-monotonic formalism to handle defeasible know

Training-free Cross-domain Few-shot Segmentation via Robust Semantic Representation and Matching

arXiv:2606.24297v1 Announce Type: new Abstract: Cross-domain Few-shot Segmentation (CD-FSS) aims to transfer knowledge learned from source domain to distinct target domains, segmenting unseen target c

Transformation Behavior of Images in Latent Space

arXiv:2606.24430v1 Announce Type: cross Abstract: Training of neural networks for histopathology classification tasks typically relies on data encoding into latent space, which reduces complexity and

Transformer-Based Language Models Across Domain Verticals: Architectures, Applications and Critical Assessment

model-releasesarxiv-cs-cl

arXiv:2606.24331v1 Announce Type: new Abstract: Transformer-based language models have become the default substrate for natural language processing and the pace of new releases has made it hard for pr

Tri-Efficient Transfer Learning for Point Cloud Videos

arXiv:2606.24175v1 Announce Type: new Abstract: While point cloud foundation models have significantly advanced point cloud video understanding, existing parameter-efficient fine-tuning (PEFT) methods

Trimming the Long-Tail of Visual World Modeling Evaluation

arXiv:2606.24256v1 Announce Type: new Abstract: Physical interactions follow a long-tailed distribution: a set of common and regular interactions dominates human experience and visual data, while a br

TrOCR for Medieval HTR: A Systematic Ablation Study with Cross-Dataset Validation

arXiv:2606.24302v1 Announce Type: new Abstract: Fine-tuning transformer-based handwritten text recognition (HTR) models on medieval manuscripts is challenging because these models are pre-trained on m

TruncProof: A Guardrail for LLM-based JSON Generation under Token-Length Constraints

arXiv:2605.13076v2 Announce Type: replace Abstract: The LLM-based generation of machine-readable outputs such as JSON has attracted significant attention for integration with external systems. However

safetyarxiv-cs-cl

Trustworthy Image Authentication using Forensic Knowledge Graphs

arXiv:2606.23917v1 Announce Type: new Abstract: Advances in generative AI have made image falsification highly realistic, demanding trustworthy authentication systems. Existing forensic detectors can

Tuning without Peeking: Provable Generalization Bounds and Robust LLM Post-Training

arXiv:2507.01752v4 Announce Type: replace-cross Abstract: Gradient-based optimization is the workhorse of deep learning, offering efficient and scalable training via backpropagation. However, exposing

Hardware

TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU

arXiv:2606.24039v1 Announce Type: new Abstract: Robotics increasingly relies on GPUs for parallel simulation, large-scale learning, and neural-network inference. For model predictive control (MPC) to

hardwarearxiv-cs-ro

Applications

TuringViT: Making SOTA Vision Transformers Accessible to All

arXiv:2606.24253v1 Announce Type: new Abstract: Modern VLMs and VLA systems commonly adopt off-the-shelf ViTs such as SigLIP2 as visual encoders, but diverse downstream requirements in latency, tempor

applicationsarxiv-cs-cv

Uncertainty-Aware Longitudinal Forecasting of Alzheimer's Disease Progression Using Deep Learning

arXiv:2606.24604v1 Announce Type: new Abstract: Longitudinal modelling of Alzheimer's disease progression is clinically useful only if it can describe not just the most likely next diagnosis, but how

Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination

arXiv:2311.02960v5 Announce Type: replace-cross Abstract: Over the past decade, deep learning has proven to be a highly effective tool for learning meaningful features from raw data. However, it remai

UniDrive: A Unified Vision-Language and Grounding Framework for Interpretable Risk Understanding in Autonomous Driving

arXiv:2606.24759v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) have shown strong potential for autonomous driving scene understanding, yet existing methods still fac

Uniform Sampling from High-dimensional Spectral Norm Balls

arXiv:2606.24134v1 Announce Type: cross Abstract: Motivated by an application in machine learning optimization, this paper focuses on the challenges of sampling a matrix uniformly from the unit spectr

researcharxiv-cs-lg

UniRED: Unified RGB-D Video Frame Interpolation with Event Guidance

arXiv:2606.24282v1 Announce Type: new Abstract: High frame-rate RGB-D videos are crucial for a variety of downstream tasks, including motion analysis, dynamic scene understanding, and 3D reconstructio

UniTranslator: A Unified Multi-modal Framework for End-to-end In-Image Machine Translation

arXiv:2606.24333v1 Announce Type: new Abstract: In-Image Machine Translation (IIMT) aims to translate scene text in an image and render the translated text back into the original regions while preserv

safetyarxiv-cs-cv

Agents

Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent

arXiv:2606.24094v1 Announce Type: new Abstract: Unifying image clustering across different clustering scenarios remains challenging due to fundamental gaps among tasks. We introduce a Guideline-Driven

agentsarxiv-cs-cv

UOL@IDEM at BEA 2026 Shared Task 1: Neural Fusion and Feature-Rich Modeling for L1-Aware Vocabulary Difficulty Prediction

arXiv:2606.24501v1 Announce Type: new Abstract: This paper describes UOL@IDEM's closed-track submission to the BEA 2026 shared task on L1-aware vocabulary difficulty prediction. We model the task as r

safetyarxiv-cs-cl

Variational Model Merging for Pareto Front Estimation in Multitask Finetuning

arXiv:2412.08147v2 Announce Type: replace-cross Abstract: Pareto fronts are useful to find good task-mixing strategies for multitask finetuning, but they are also costly to compute. To reduce costs, r

Agents

Varying Bundle Size Reactive Multi-Task Assignment using Selective Cost Estimation for Multi-Agent Systems

arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall

agentsarxiv-cs-ro

Verifiable Foundation Models for Robot Safety

arXiv:2606.23754v1 Announce Type: cross Abstract: Deploying foundation models for robot control raises a central challenge: the expressive power that enables rich, multimodal perception also makes the

safetyarxiv-cs-lg

VeriPilot: An LLM-Powered Verilog Debugging Framework

arXiv:2606.23759v1 Announce Type: cross Abstract: Verilog debugging remains one of the most time-consuming stages in digital circuit design. Recent advances in Large Language Models (LLMs) have enable

VeryTrace: Verifying Reasoning Traces through Compilable Formalism and Structured Verification

arXiv:2606.24124v1 Announce Type: new Abstract: Multi-step reasoning with Chain-of-Thought (CoT) prompting remains fragile: logical errors or hallucinations in early steps silently propagate, producin

video-SALMONN-R^3: Learning to ReWatch, ReAsk, and ReAnswer for Efficient Video Understanding

arXiv:2606.24477v1 Announce Type: cross Abstract: Video large language models (LLMs) are often constrained by computation and memory budgets, leading them to use reduced frame rates and spatial resolu

VieSpeaker: A Large-Scale Vietnamese Speaker Recognition Dataset Beyond Visual Dependency

arXiv:2606.24066v1 Announce Type: cross Abstract: Speaker recognition has advanced rapidly with large-scale training datasets, yet Vietnamese remains under-resourced, with existing corpora limited in

researcharxiv-cs-cl

Applications

VisChronos: Revolutionizing Image Captioning Through Real-Life Events

arXiv:2606.24058v1 Announce Type: new Abstract: This paper aims to bridge the semantic gap between visual content and natural language understanding by leveraging historical events in the real world a

applicationsarxiv-cs-cv

VisCritic: Visual State Comparison as Process Reward for GUI Agents

arXiv:2606.24525v1 Announce Type: new Abstract: GUI agents powered by vision-language models show strong potential for automating digital tasks, yet frequently fail in long-horizon scenarios due to th

Agents

Vision-Language Model Reasoning for Contextual Semantic Mapping in Intralogistics

arXiv:2606.24814v1 Announce Type: new Abstract: Autonomous mobile robots operating in intralogistics environments rely on geometric maps for localization and navigation, but lack semantic understandin

agentsarxiv-cs-ro

Local Ai

VistaRef: Boosting Visual Spatial Orientation Awareness for Pointing-to-Object Detection

arXiv:2606.24498v1 Announce Type: new Abstract: Grounding deictic gestures in natural images is fundamental to AR and human-robot collaboration, providing a basis for seamless spatial interaction. Whi

local-aiarxiv-cs-cv

Visualizing 'We the People': Bridging the Perception Gap through Pluralistic Data Storytelling

arXiv:2606.24635v1 Announce Type: cross Abstract: Traditional visual data storytelling relies on binary graphics that depict two simplified groups in conflict. This can increase political polarization

Applications

ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering

arXiv:2606.24602v1 Announce Type: new Abstract: Despite remarkable progress in multimodal understanding, current MLLMs still exhibit limitations in video text understanding, particularly when semantic

applicationsarxiv-cs-cv

Hardware

VoltanaLLM: Energy-Efficient and SLO-Aware Disaggregated LLM Serving via Adaptive Frequency Control and State-Space Routing

arXiv:2509.04827v3 Announce Type: replace-cross Abstract: The energy cost of Large Language Model (LLM) inference is rapidly becoming a barrier to sustainable and scalable deployment. Although modern

hardwarearxiv-cs-ai

VSANet: View-aware Sparse Attention Network for Light Field Image Denoising

arXiv:2606.24737v1 Announce Type: new Abstract: Light field (LF) image denoising is challenging due to the high-dimensional structure of LF data. While noise is independent across sub-aperture images,

Weight-Space Geometry of Offline Reasoning Training

arXiv:2606.23740v1 Announce Type: cross Abstract: Offline reinforcement-learning losses (RFT, RIFT, DFT, Offline GRPO, DPO) are widely used to distill reasoning from large teachers into smaller studen

What Do Flow-Based Inverse Solvers Approximate? A Posterior-Transport View

arXiv:2606.24516v1 Announce Type: new Abstract: A growing family of training-free solvers -- FlowDPS, FLOWER, PnP-Flow and their diffusion ancestors (DPS, DAPS) -- repurpose a pretrained flow-matching

safetyarxiv-cs-cv

What Does ODRL Mean? A Cross-Level Ontological Grounding of Permissions, Prohibitions, and Duties in UFO-L

arXiv:2606.24344v1 Announce Type: cross Abstract: ODRL policy evaluators produce verdicts, but say nothing about the normative positions a policy brings into existence, the authority structures those

What's Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning

arXiv:2506.00869v3 Announce Type: replace Abstract: Despite the impressive performance of vision-language models (VLMs) on downstream tasks, their ability to understand and reason about causal relatio

researcharxiv-cs-cl

When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

arXiv:2407.18957v5 Announce Type: replace-cross Abstract: Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroe

safetyarxiv-cs-ai

When CQs Go Wrong: Challenges in CQ Verification with OE-Assist

arXiv:2606.24619v1 Announce Type: new Abstract: Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natur

safetyarxiv-cs-ai

When Helpfulness Overrides Causal Caution: Context-Dependent Suppression and Recovery in LLMs

arXiv:2606.24370v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into decision-support roles in business and policy contexts. While prior benchmark studies have

When Preferences Fail to Become Incentives: A Utility-Behavior Gap in Large Language Models

arXiv:2606.22974v2 Announce Type: replace Abstract: Recent work on preference elicitation in large language models (LLMs) has demonstrated that, when given a series of choices between two outcomes, LL

safetyarxiv-cs-ai

When Retrieval Metrics Mislead: Measuring Policy Signal in Long-Horizon Tool-Use Agents

arXiv:2606.23937v1 Announce Type: cross Abstract: Exact-match retrieval recall is often used as a proxy for whether a retriever supplies useful policy context to a downstream decision model. We test t