Search: “framework”

Local MDI+: Local Feature Importances for Tree-Based Models

arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp

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Locality-Aware Redundancy Pruning for LLM Depth Compression

DGX agent

arXiv:2605.27786v1 Announce Type: cross Abstract: Large language models are known to contain representational redundancy across network depth, making depth pruning an effective approach for improving

local-aiarxiv-cs-ai

28 May 2026

Local Ai

Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values

arXiv:2605.28170v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a

local-aiarxiv-cs-ai

Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization

arXiv:2605.28109v1 Announce Type: new Abstract: Recent advances in online reinforcement learning (RL) for large language models (LLMs) have demonstrated promising performance in complex reasoning task

safetyarxiv-cs-lg

LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts

arXiv:2602.11564v2 Announce Type: replace Abstract: Recent advances in video diffusion models have significantly improved visual quality, yet ultra-high-resolution (UHR) video generation remains a for

LV-OSD: Language-Vision-Complementary Open-Set Object Detection

arXiv:2605.28271v1 Announce Type: new Abstract: Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images.

Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning

arXiv:2605.27960v1 Announce Type: new Abstract: Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoni

Tutorials

Majorization-Minimization Networks for Inverse Problems: An Application to EEG Imaging

arXiv:2602.03855v2 Announce Type: replace-cross Abstract: Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based a

tutorialsarxiv-cs-lg

MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation

arXiv:2502.12468v2 Announce Type: replace-cross Abstract: The LLM-as-a-Judge paradigm shows promise for evaluating generative content but lacks reliability in reasoning-intensive scenarios, such as pr

researcharxiv-cs-ai

MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models

arXiv:2605.28009v1 Announce Type: cross Abstract: Memory-augmented large language models extend reasoning beyond a fixed context window by maintaining long-term memory across interactions. However, ex

MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems

arXiv:2605.28732v1 Announce Type: cross Abstract: Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult

MERIT: Matching Expertise via Rubric-Informed Training for Reviewer Assignment

arXiv:2605.27865v1 Announce Type: new Abstract: Matching submissions with suitable reviewers at scale is a growing challenge for major venues, yet existing approaches either rely on coarse proxy signa

researcharxiv-cs-cl

Meta-Attention: Bayesian Per-Token Routing for Efficient Transformer Inference

arXiv:2605.28384v1 Announce Type: new Abstract: Standard transformer architectures apply a single attention mechanism uniformly across all tokens and sequence positions, irrespective of local context

Metric-Aware PCA as a Linear Instance of Geometric Deep Learning

arXiv:2605.27456v1 Announce Type: new Abstract: Geometric deep learning organises neural architectures around the symmetries of their data domain, with the choice of symmetry group serving as a geomet

researcharxiv-cs-lg

Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification

arXiv:2605.28604v1 Announce Type: cross Abstract: Identifying key individuals in video scenes is essential for applications such as automated video editing and intelligent surveillance. Current method

safetyarxiv-cs-ai

Mitigating Cross-Lingual Cultural Inconsistencies in LLMs via Consensus-Driven Preference Optimisation

arXiv:2605.12515v2 Announce Type: replace Abstract: Despite their impressive capabilities, multilingual large language models (MLLMs) frequently exhibit inconsistent behaviour when the prompt's langua

safetyarxiv-cs-cl

Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation

arXiv:2602.03515v2 Announce Type: replace-cross Abstract: Asynchronous pipeline parallelism maximizes hardware utilization by eliminating the pipeline bubbles inherent in synchronous execution, offeri

Moment Matters: Mean and Variance Causal Graph Discovery from Heteroscedastic Observational Data

arXiv:2602.23602v2 Announce Type: replace-cross Abstract: Heteroscedasticity -- where the variance of a variable changes with other variables -- is pervasive in real data, and elucidating why it arise

MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations

arXiv:2605.28261v1 Announce Type: new Abstract: Instance-level quantification of kidney functional units is essential for morphometric analysis, yet most publicly available pathology datasets provide

Agents

MRMMIA: Membership Inference Attacks on Memory in Chat Agents

arXiv:2605.27825v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) test whether a target data record belongs to a system's private data, and have become a standard tool to measure p

agentsarxiv-cs-lg

MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation

arXiv:2605.28579v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Ex

Natural Functional Gradients for Smooth Trajectory Optimization

arXiv:2605.28202v1 Announce Type: new Abstract: Generating collision-free and smooth motions remains a central challenge in robotic manipulation, particularly in cluttered environments and narrow pass

researcharxiv-cs-ro

Neural Weight Compression for Language Models

arXiv:2510.11234v3 Announce Type: replace Abstract: Efficient compression of language model weights is increasingly critical as model scale and deployment grow. Yet, most existing methods rely on hand

researcharxiv-cs-lg

Next-Scale Autoregressive Models for Text-to-Motion Generation

arXiv:2604.03799v2 Announce Type: replace Abstract: Autoregressive (AR) models offer stable and efficient training, but standard next-token prediction is not well aligned with the temporal structure r

NL-MambaXCT: Self-Supervised Nested-Learning Mamba for Nomex Honeycomb X-ray CT Defect Classification

arXiv:2605.27454v1 Announce Type: cross Abstract: X-ray computed tomography (XCT) is widely used for non-destructive testing of Nomex honeycomb structures in aerospace manufacturing, but industrial in

No Certificate for Alignment: Two Independent Impossibilities and the Pareto Frontier of Achievable Safety Guarantees

arXiv:2603.08761v2 Announce Type: replace-cross Abstract: We argue that formal certification of AI alignment over open-ended or unbounded input domains is impossible under standard assumptions in comp

safetyarxiv-cs-lg

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels

arXiv:2511.18894v5 Announce Type: replace-cross Abstract: Medical image segmentation is crucial for clinical applications, but it is frequently disrupted by noisy annotations and ambiguous anatomical

OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings

arXiv:2605.28168v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising capability in generating reward functions for deep reinforcement learning (DRL)-based building

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning

arXiv:2604.18530v2 Announce Type: replace Abstract: Recent advancements in Reinforcement Learning with Verifiable Rewards (RLVR) have significantly improved Large Language Model (LLM) reasoning, yet m

safetyarxiv-cs-ai

{Omega}-QVLA: Robust Quantization for Vision-Language-Action Models via Composite Rotation and Per-step Scaling

arXiv:2605.28803v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control within a single policy, yet their multi-billion-parameter backbones and dif

OralAgent: Integrating Reasoning, Tools, and Knowledge for Interactive Dental Image Analysis

model-releasesarxiv-cs-cl

arXiv:2605.27378v1 Announce Type: new Abstract: Dental image analysis plays a pivotal role in supporting accurate diagnosis and treatment planning in oral healthcare. Although recent advances have pro

Agents

Out of Sight, Not Out of Mind: Unveiling Latent Attack in Latent-based Multi-Agent Systems

arXiv:2605.28214v1 Announce Type: cross Abstract: Latent-based multi-agent systems replace parts of explicit inter-agent communication with hidden representations, offering a new direction for efficie

agentsarxiv-cs-lg

Particle-Guided Diffusion Models for Partial Differential Equations

arXiv:2601.23262v2 Announce Type: replace Abstract: We introduce a guided stochastic sampling method that augments sampling from diffusion models with physics-based guidance derived from partial diffe

Pattern Recognition Tasks with Personalized Federated Learning

arXiv:2605.27816v1 Announce Type: new Abstract: Personalized Federated Learning (PFL) constitutes a novel paradigm that tailors Machine Learning (ML) models to individual clients, thereby furnishing p

Agents

Personality, Role, and Expressive Style in Large Language Models: An Interactionist Analysis

arXiv:2605.28037v1 Announce Type: new Abstract: Prompt-based personality control is a key technique for designing large language model (LLM) dialogue agents that behave consistently across social cont

agentsarxiv-cs-cl

PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion

arXiv:2605.28226v1 Announce Type: new Abstract: Small-molecule drug discovery requires simultaneous optimization of numerous properties of candidate molecules. These properties can be investigated thr

researcharxiv-cs-lg

Picid: A Modular Evaluation Infrastructure for Reproducible PHM Across Tasks and Domains

arXiv:2605.28345v1 Announce Type: new Abstract: Progress in Prognostics and Health Management (PHM) is hindered by the lack of standardized and reusable evaluation practices across tasks, datasets, an

safetyarxiv-cs-ai

Prefix-Safe Bayesian Belief Tracking for LLM Reasoning Reliability:Separating Calibration from Ranking

arXiv:2605.27712v1 Announce Type: new Abstract: Long reasoning traces need reliability estimates before final answers are known. We study prefix-conditioned eventual-success estimation, P(y=1 mid o_{1

researcharxiv-cs-ai

Privacy Protection Against Personalized Text-to-Image Synthesis via Cross-image Consistency Constraints

arXiv:2504.12747v2 Announce Type: replace Abstract: The rapid advancement of diffusion models and personalization techniques has made it possible to recreate individual portraits from just a few publi

Privately Estimating Monotone Statistics in Polynomial Time

arXiv:2605.27912v1 Announce Type: cross Abstract: We study efficient differentially private algorithms for estimating monotone statistics, i.e., statistics that are monotone under the addition of new

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP

arXiv:2605.27527v1 Announce Type: cross Abstract: Astrophysical observations taken from Earth are subject to weather, environmental, and scientific constraints that lead to sparse, irregular light cur

Probing for Knowledge Attribution in Large Language Models

arXiv:2602.22787v2 Announce Type: replace-cross Abstract: Large language model (LLM) hallucinations, meaning fluent but factually incorrect generations, fall into two types: faithfulness violations, w

Prompt Codebooks: Discrete Compositional Optimization for Language Model Instruction Refinement

arXiv:2605.28360v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has driven significant gains in LLM-based agentic workflows. However, existing methods treat each task's prompt as a

PromptEmbedder:: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting

arXiv:2605.28066v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable efficacy in text embedding, yet current adaptation methods like LoRA face significant bottle

Proprio: Latent Self-Scoring and Inference-Time Refinement for Physically Plausible Video Generation

arXiv:2605.28230v1 Announce Type: new Abstract: Modern video generative models produce visually impressive results, yet frequently violate basic physical principles. We propose Proprio, a training-fre

ProvMind: Provenance-grounded reasoning for materials synthesis

arXiv:2605.28487v1 Announce Type: new Abstract: Materials process optimization requires reasoning over routes, conditions, tools and causal dependencies, yet most computational formulations flatten sy

PrunePath: Towards Highly Structured Sparse Language Models

arXiv:2605.28283v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate the parameter count and computation of modern language models, yet existing pruning methods often struggle to co

Pruning and Distilling Mixture-of-Experts into Dense Language Models

arXiv:2605.28207v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory,