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Life-Bench: A Benchmark and Knowledge Graph Framework for Multimodal Personalization Beyond Concept Recognition

arXiv:2602.19001v2 Announce Type: replace Abstract: As large language models increasingly power personal assistants, users expect them to reason over multimodal life histories, from recognizing people

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Research

Lifted Model Construction under Approximate Commutativity

DGX agent

arXiv:2608.24713v1 Announce Type: new Abstract: Lifted inference algorithms enable scalable probabilistic inference even for large object domains by leveraging the indistinguishability of objects in a

researcharxiv-cs-ai

26 Aug 2026

Lightweight GenAI for Network Traffic Generation: Fidelity, Augmentation, and Classification

arXiv:2603.25507v2 Announce Type: replace-cross Abstract: Network Traffic Classification (NTC) increasingly relies on data-driven models, yet its practical deployment is often constrained by limited l

LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning

arXiv:2608.24795v1 Announce Type: new Abstract: Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to multim

LLM Agents Perform Controlled Experiments Using Simulation Models

arXiv:2608.23622v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more

LLM-Guided Contextual Action Evaluation for Operational Decisions in Industrial Processes

arXiv:2608.24156v1 Announce Type: cross Abstract: Industrial actor--critic methods usually represent continuous actions as anonymous numerical coordinates. They must therefore learn from limited inter

Local Ai

Look as You Leap: Planning Simultaneous Motion and Perception for High-DOF Robots

arXiv:2509.19610v3 Announce Type: replace Abstract: Most common tasks for robots in dynamic spaces require that the environment is regularly and actively perceived. The perception task considered in t

local-aiarxiv-cs-ro

Low-Latency Activation-Regularized Sparse Neural Operators with Distillation Assistance Towards Real-Time Edge-Deployable Virtual Sensing

arXiv:2608.23987v1 Announce Type: new Abstract: Virtual sensing enables digital twins and safety-critical systems to reconstruct and forecast spatial-temporal physics in real time. However, convention

Low-Rank Ternary Adaptation for Fine-Tuning Transformers

arXiv:2608.24469v1 Announce Type: new Abstract: Ternary transformers offer extreme memory and compute efficiency, but existing low-bit LoRA-based methods cannot directly fine-tune ternary weights. Cur

Local Ai

Low-Rank Velocity Fields as a Structural Prior for Unsupervised 4D Medical Image Interpolation

arXiv:2608.24025v1 Announce Type: new Abstract: Endpoint-only unsupervised 4D medical image interpolation synthesizes intermediate volumes from sparsely sampled sequences with only the start and end v

local-aiarxiv-cs-cv

Agents

LUCAID: Agentic Multimodal AI for Lung Cancer Precision Pathology

arXiv:2608.23803v1 Announce Type: cross Abstract: Lung cancer tissue diagnostics is complex, as therapy decisions in precision oncology rely on the integration of histomorphological, immunohistochemic

agentsarxiv-cs-ai

Luce: Relightable Gaussians for 3D Asset Generation

arXiv:2608.23943v1 Announce Type: cross Abstract: High-fidelity image-to-3D generation requires a 3D representation that captures both geometry and appearance. To support relighting and integration in

LumiXAI: A Modular Full-Stack Framework for Feature Attribution

arXiv:2608.24524v1 Announce Type: cross Abstract: Feature attribution is a central tool of model interpretability, yet the software through which it is applied remains fragmented: individual tools spe

LUX: A Lesion-Aware Graph-Conditioned Visual - Language Architecture for Explainable Endoscopic Captioning

arXiv:2608.23853v1 Announce Type: new Abstract: The interpretation of endoscopic imagery in ulcerative colitis is complex and subjective, with variability in human assessment and subtle mucosal inflam

safetyarxiv-cs-cv

Tutorials

Macro-Operator Generation and Predicate Selection for TAMP Operator Learning

arXiv:2608.23629v1 Announce Type: cross Abstract: Creating symbolic operators by hand is one of the main bottlenecks in deploying Task and Motion Planning systems (TAMP). Recent works show that these

tutorialsarxiv-cs-ai

Mahalanobis-Based Multi-Head Attention for Complex State Propagation

arXiv:2608.24462v1 Announce Type: new Abstract: In this paper, we propose extbf{Mahalanobis-Based Multi-Head Attention} (MHA-CSP), a novel attention mechanism that replaces the standard dot-product wi

Local Ai

Maia 200: A Software Defined Dataflow System for Large-scale AI Acceleration

arXiv:2608.24664v1 Announce Type: cross Abstract: We introduce Maia 200, an advanced AI accelerator delivering high performance-10 145 Tflop/s FP4 and 5072 Tflop/s FP8 within a 750W TDP and 7 TB/s HBM

local-aiarxiv-cs-ai

Applications

Markerless Pose Estimation for Resistance Training Technique Assessment

arXiv:2608.24384v1 Announce Type: cross Abstract: Resistance training can be a high risk activity, and safe form is essential to avoiding injury. Laboratory-based movement analysis provides quantitive

applicationsarxiv-cs-ai

MARS: Multi-Specialist LLM Relay System for Competitive Programming

arXiv:2608.23918v1 Announce Type: new Abstract: Large Language Models excel at code generation, yet competitive programming exposes a persistent failure mode: existing multi-agent pipelines distribute

Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks

arXiv:2505.11239v4 Announce Type: replace Abstract: Understanding human mobility through Point-of-Interest (POI) trajectory modeling is increasingly important for applications such as urban planning,

MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking

arXiv:2608.24365v1 Announce Type: new Abstract: Transformer-based object trackers are renowned for their strong performance, yet dense token processing often leads to prohibitive computational cost, l

researcharxiv-cs-cv

Matched Excess-Outranker Regularization for Candidate-Set Interference in Continual Knowledge Graph Embedding

arXiv:2608.24273v1 Announce Type: new Abstract: Continual knowledge graph embedding updates entity and relation representations as a graph grows. Existing methods primarily address catastrophic forget

MatReplace: A Reference-Free, Conditioning-Aligned Benchmark for Material Replacement in Interior Scenes

arXiv:2608.24107v1 Announce Type: cross Abstract: Material replacement is a common interior-design operation: changing the material of a selected surface while preserving its geometry, surroundings, a

Tutorials

MDTE: Minority-Aware Diffusion over Temporal Edge Events for Imbalanced Node Classification

arXiv:2608.24812v1 Announce Type: new Abstract: Class-imbalanced node classification on temporal graphs is challenging because majority-dominated temporal propagation progressively assimilates minorit

tutorialsarxiv-cs-lg

Mechanistic Circuit Identification for Controllable Data Generation

arXiv:2608.24065v1 Announce Type: cross Abstract: While recent advances in data synthesis aim to curate high-quality datasets, most generation pipelines still rely on heuristic prompt-based control. T

Memory Is Not Always Needed: Characterizing Conditional Memory in Scientific Reasoning

arXiv:2608.23982v1 Announce Type: new Abstract: Scientific reasoning requires language models to retrieve specialized knowledge and incorporate it reliably into multi-step computation. Conditional mem

Metadata-Aware Adaptation of a Generative Foundation Model for Conditional CMR Synthesis

arXiv:2608.24342v1 Announce Type: cross Abstract: Synthetic image generation is a promising strategy to address data scarcity and the underrepresentation of clinically important phenotypes in medical

Meta^n: Recursive Self-Improvement through Emergent Depth

arXiv:2608.24735v1 Announce Type: new Abstract: Self-improving LLM agents refine answers, not the process that produces those answers. Systems that add a meta-level hold that level fixed, and those th

MetaRAG: Belief-Action Aligned Policy Optimization for Agentic RAG

arXiv:2608.24214v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) requires language models to decide when to continue searching and when to answer. Existing RL-based methods

Method, Mind, and Morality: How People Make Sense of Artificial Intelligence

arXiv:2608.24748v1 Announce Type: cross Abstract: How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixed

Mind the Student: Behavioral and Contextual Cues for Automated Engagement Prediction in Online Learning

arXiv:2608.24340v1 Announce Type: cross Abstract: The prediction of student engagement from the online tutoring videos is difficult because engagement is a multidimensional construct comprising distin

Hardware

Minima-KV: Retention-Preserving KV Cache Compression with Mixed-Format Paged Attention

arXiv:2608.23834v1 Announce Type: new Abstract: The key-value (KV) cache is a primary capacity and bandwidth bottleneck in long-context LLM serving. We present Minima-KV, a retention-preserving hierar

hardwarearxiv-cs-ai

Minimal Decision Dynamics and Contextual Probability: A Quantum Tug-of-War Model

arXiv:2601.10034v3 Announce Type: replace-cross Abstract: Decision making often exhibits context dependence that is difficult to accommodate within a single non-invasive classical probability model. T

(Mis)Understanding Benign Overfitting in Equity Return Prediction

arXiv:2608.23761v1 Announce Type: cross Abstract: Highly overparameterized models often predict well despite interpolating training data in complex domains, challenging the classical bias--variance tr

Mitigating Exploration Bias in RL for Multi-Instruction Following

arXiv:2608.23830v1 Announce Type: cross Abstract: RL has emerged as a powerful paradigm for enhancing the instruction following capabilities of LLMs. While existing training recipes achieve substantia

Tutorials

Mixture of Channel Experts: Static Sparse Supports with Input-Adaptive Mixing for Pointwise Projections

arXiv:2608.23794v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) scales language models by routing each input through a small set of independently parameterized experts. We show that copying

tutorialsarxiv-cs-cv

MnemoDyn: Learning Resting State Dynamics from 40K FMRI sequences

arXiv:2608.23936v1 Announce Type: new Abstract: We present a dynamical-systems based model for resting-state functional magnetic resonance imaging (rs-fMRI), trained on a dataset of roughly 40K rs-fMR

researcharxiv-cs-lg

Model-Based Learning of Near-Optimal Finite-Window Policies in POMDPs

arXiv:2604.01024v2 Announce Type: replace Abstract: We study model-based learning of finite-window policies in tabular partially observable Markov decision processes (POMDPs). A common approach to lea

researcharxiv-cs-lg

Model Effect or Label Effect? Refined Annotations and a Human-Referenced Benchmark for Pulmonary Embolism Segmentation

arXiv:2608.24486v1 Announce Type: cross Abstract: Purpose: To quantify how evaluation annotations influence measured pulmonary embolism (PE) segmentation performance relative to model training changes

MoE-based Feature Adapter for Prompt-free Binary Coronary Artery Segmentation in X-ray Angiography

arXiv:2608.24783v1 Announce Type: new Abstract: Accurate segmentation of coronary arteries in X-ray angiography videos is essential for quantitative coronary analysis and image-guided interventions. H

MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models

arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation

MolGA: Molecular Graph Adaptation with Pre-trained 2D Graph Encoder

arXiv:2510.07289v2 Announce Type: replace Abstract: Molecular graph representation learning is widely used in chemical and biomedical research. While pre-trained 2D graph encoders have demonstrated st

More GPUs or a Smaller Cache? Tensor Parallelism versus KV Compression for Memory-Bound LLM Serving

arXiv:2608.23962v1 Announce Type: new Abstract: When an LLM serving deployment runs out of KVcache room, there are two well-established ways out. Tensor parallelism shards the weights and the KV cache

More Motion Is Not Always Better Motion: Corpus Composition Governs Whether Augmentation Helps SMPL-Based Parkinsonian Gait Severity Estimation

arXiv:2608.23730v1 Announce Type: new Abstract: We grade MDS-UPDRS gait severity from SMPL motion using three frozen MotionAGFormer encoders as featurizers, reaching macro-F1 0.58 on a hidden, multi-s

researcharxiv-cs-cv

More Rejective, Not More Discriminative: The Unit of Verification in Pre-Execution LLM Oversight

arXiv:2608.23941v1 Announce Type: new Abstract: Pre-execution oversight is core to trusted monitoring in AI control: a fallible LLM monitor vets planned actions before irreversible execution. Over-blo

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

MoTE: Mixture of Task Experts for Multi-Task Video Understanding

arXiv:2608.24763v1 Announce Type: new Abstract: Procedural video-language models must solve heterogeneous tasks from the same visual evidence, including action recognition, forecasting, and procedure

researcharxiv-cs-cv

MPIB: A Benchmark for Medical Prompt Injection Attacks and Clinical Safety in LLMs

arXiv:2602.06268v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows. However, pr