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LDU-Bench: Multimodal LLM Evaluation for Lithography Defect Understanding under Layout-Varying Circuit Backgrounds

arXiv:2608.03078v1 Announce Type: new Abstract: Multimodal large language models have demonstrated strong defect recognition capability in industrial anomaly detection. However, in lithography review,

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Model Releases

LeanMem: Simple and Efficient Long-Term Memory for LLM Agents

DGX agent

arXiv:2608.03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history. However, existing memory systems typic

model-releasesarxiv-cs-ai

5 Aug 2026

Learning a Vector-Symbolic Model for Socio-Cultural Tasks

arXiv:2608.02807v1 Announce Type: cross Abstract: How can we better represent the impact of sociocultural structures on decision making in computational cognitive models? Modeling this impact requires

Hardware

Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling

arXiv:2608.03696v1 Announce Type: new Abstract: This work focuses on the problem of learning on temporal graphs, with particular emphasis on the task of clustering: obtaining coarse-grained representa

hardwarearxiv-cs-lg

Learning Attribute-aware Representations for Few-shot Scene Text Segmentation

arXiv:2504.11164v2 Announce Type: replace Abstract: Supervised scene text segmentation has achieved notable progress in recent years. However, its development is largely constrained by the scarcity of

safetyarxiv-cs-cv

Learning Biomechanically Plausible Human Motion from Sparse Radar Point Clouds

arXiv:2608.03637v1 Announce Type: new Abstract: Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We add

researcharxiv-cs-cv

Learning Clinical-Trial Strategy: Offline Policy Training for Decision Agents

arXiv:2608.03606v1 Announce Type: new Abstract: Clinical development is sequential decision-making under uncertainty, where a sponsor must plan a portfolio of experiments from heterogeneous evidence.

Learning Context-Aware Motion Priors for Humanoid Control

arXiv:2608.03234v1 Announce Type: new Abstract: Motion priors provide powerful guidance for learning naturalistic humanoid behaviors. However, existing methods typically learn a general, task-agnostic

safetyarxiv-cs-ro

Learning Molecular Representations from Cellular Phenotypes with Structure Preservation

arXiv:2608.02688v1 Announce Type: cross Abstract: Phenotypic drug discovery enables the discovery of functional relationships between molecular structures and cellular responses. However, existing mul

Learning Music Style for Piano Arrangement Through Cross-Modal Bootstrapping

arXiv:2608.03050v1 Announce Type: cross Abstract: What is music style? Though often described using text labels such as 'swing,' 'classical,' or 'emotional,' the real style remains implicit and hidden

Less Traffic, Better Outcomes: Competition-Aware Request Dispatch in Real-Time Ad Exchanges

arXiv:2608.03705v1 Announce Type: new Abstract: Real-time bidding (RTB) ad exchanges typically forward nearly all incoming requests to demand-side platforms (DSPs), even though only a small fraction r

Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification

arXiv:2608.03489v1 Announce Type: cross Abstract: Combining Bayesian learning and quantitative verification is a powerful toolset for analysing key quantitative properties of software systems, like re

applicationsarxiv-cs-ai

Light-Loco-Parkour: Versatile Perceptive Whole-Body Locomotion via Multi-Skill Distillation

arXiv:2608.02653v1 Announce Type: new Abstract: Existing humanoid whole-body control systems still fall short of the way humans move through cluttered terrain: they either track expressive whole-body

safetyarxiv-cs-ro

Lightweight 3D Object Detection via Mamba-Based Knowledge Distillation

arXiv:2608.03490v1 Announce Type: cross Abstract: 3D object detection using light detection and ranging (LiDAR) sensors requires a balance between accuracy and computational efficiency for onboard per

safetyarxiv-cs-cv

Lightweight Chunk Selection for Mobile Retrieval-Augmented Generation

arXiv:2608.03148v1 Announce Type: cross Abstract: RAG improves the factual grounding of LLM by incorporating external knowledge, but deploying RAG on mobile and edge devices remains challenging becaus

Hardware

LiLa-WAM: Lightweight Latent Reasoning World-Action Model for Robotic Manipulation

arXiv:2608.03701v1 Announce Type: cross Abstract: World-action modeling has emerged as a promising paradigm for robotic control, as it empowers models to go beyond reacting to observations and anticip

hardwarearxiv-cs-ai

LiteMVS: Efficient Multi-View Stereo with Foundation Distillation and Expert Aggregation

arXiv:2608.03851v1 Announce Type: new Abstract: Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods pri

researcharxiv-cs-cv

Agents

LiveEvalBench: Toward Open-World Evaluation for Web Generation

arXiv:2608.03689v1 Announce Type: new Abstract: Large language models are increasingly capable of synthesizing executable frontend projects, yet existing benchmarks still treat web generation as a sta

agentsarxiv-cs-ai

LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models

arXiv:2608.03457v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dL

LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation

arXiv:2608.03382v1 Announce Type: cross Abstract: Multi-armed bandit algorithms, especially Thompson sampling, are widely used in online recommendation. Despite their ability to adapt from online feed

safetyarxiv-cs-lg

Hardware

LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs

arXiv:2608.03036v1 Announce Type: cross Abstract: Large Language Models (LLMs) are integrated into software systems and AI services, making efficient LLM serving a concern for software engineering. Se

hardwarearxiv-cs-ai

LLMs Can Annotate Attribution Graphs

arXiv:2608.02632v1 Announce Type: new Abstract: Circuit tracing is an exciting technique for revealing the internal computation of language models, but it requires a time-intensive manual step of grou

researcharxiv-cs-lg

Local Ai

LoBoost: Fast Model-Native Local Conformal Prediction for Gradient-Boosted Trees

arXiv:2602.22432v2 Announce Type: replace-cross Abstract: Gradient-boosted decision trees are among the strongest off-the-shelf predictors for tabular regression, but point predictions alone do not qu

local-aiarxiv-cs-lg

LoCA: Forward-Only LLM Tuning after One-Shot Calibration with Local Credit Assignment

arXiv:2608.03020v1 Announce Type: new Abstract: Parameter-efficient post-training reduces the number of trainable parameters, but still requires repeated end-to-end backpropagation through the frozen

Localize, Don't Beautify: Client-Side Control of Image-Editing APIs for Cosmetic Surgery Previews

arXiv:2608.02841v1 Announce Type: new Abstract: Ask a commercial image editor to preview a cosmetic procedure and it will often change more of the face than the request names: a nose edit can also smo

LocAnyMed: Vision-Language Grounding for Multimodal Medical Images

arXiv:2608.03322v1 Announce Type: new Abstract: Medical visual grounding connects free-form clinical queries to spatial evidence in medical images and is an important component of interpretable medica

Logic Before Language: Pre-pretraining on Formal Derivations Fosters Skill Acquisition and Compressibility

arXiv:2608.03930v1 Announce Type: cross Abstract: Pre-pretraining language models (LMs) on symbolic data can accelerate and improve natural language acquisition. However, existing pre-pretraining task

LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics

arXiv:2603.24929v2 Announce Type: replace Abstract: Understanding and quantifying uncertainty in large language model (LLM) outputs is critical for reliable deployment. However, traditional evaluation

applicationsarxiv-cs-ai

Long-term Traffic Scene Prediction via Polynomial Representations in Autonomous Driving

arXiv:2608.03330v1 Announce Type: new Abstract: This thesis addresses fundamental challenges in traffic scene prediction for autonomous driving by introducing robust and computationally efficient mode

Looking under the Wrong Lamppost: On the Limitations of Automated Translation Quality Estimation

arXiv:2608.03577v1 Announce Type: new Abstract: Automation of Translation Quality Estimation (QE) has emerged as a widely discussed approach to managing translation quality at scale, and a growing num

LoopMTP: A looped transformer guided by latent multi-token prediction

arXiv:2608.03624v1 Announce Type: new Abstract: Looped transformers have emerged as a parameter-efficient alternative to scaling depth for strong reasoning. By reusing one stack of layers across T ite

Low-Dimensional High-Leverage Subspace Optimization: Beyond Full-Parameter Coupled Training for Neural Network Quantization

arXiv:2608.03919v1 Announce Type: new Abstract: Low-bit quantization suffers severe accuracy degradation on compact networks, rooted in the dominant full-parameter coupled training paradigm that ignor

M-GATE: Multilingual Grammar, Accuracy in Translation, and Efficiency Benchmark for Large Language Models

arXiv:2608.03803v1 Announce Type: new Abstract: Multilingual language models are deployed across a hundred or more languages, yet most benchmarks test whether a model can perform a task _in_ a languag

Agents

MAFIA: Query-Only Memory Attacks via Probing and Factual Injection against Audited LLM Agents

arXiv:2608.03844v1 Announce Type: new Abstract: Memory-augmented LLM agents rely on rich context for long-horizon reasoning and acting, yet their memory modules expose a persistent attack surface for

agentsarxiv-cs-ai

Maglev: Sliding Recurrent Memory

model-releasesarxiv-cs-lg

arXiv:2608.02870v1 Announce Type: new Abstract: We introduce ours{}, a recurrent Transformer architecture with fixed-size memory that generalizes sliding-window attention while remaining parallelizabl

MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting

arXiv:2405.16440v2 Announce Type: replace-cross Abstract: In recent years, Transformers have become the de-facto architecture for long-term time series forecasting (LTSF), yet they face challenges ass

Mapping the City Through the Lens of Language Models

arXiv:2608.02971v1 Announce Type: new Abstract: Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and

researcharxiv-cs-cl

Material-Segmented Per-Pixel Emissivity Correction for Thermographic Anomaly Detection in Cultural Heritage Digital Twins

arXiv:2608.02964v1 Announce Type: new Abstract: Quantitative longwave thermography of heritage surfaces is limited by the global-constant emissivity assumption in inverse-Planck temperature retrieval;

MaterialFusion: High-Quality, Zero-Shot, and Controllable Material Transfer with Diffusion Models

arXiv:2502.06606v3 Announce Type: replace Abstract: Manipulating the material appearance of objects in images is critical for applications like augmented reality, virtual prototyping, and digital cont

applicationsarxiv-cs-cv

MDArena: Evaluating Coding Agents on Realistic Molecular Dynamics Workflows

arXiv:2608.02642v1 Announce Type: cross Abstract: Accelerating scientific discovery is among the most consequential applications of AI, and computational biomolecular simulation stands out as a partic

MDLMPE: Distribution Aware Positional Encoding for Masked Diffusion Language Models

arXiv:2608.03769v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) enable parallel generation and bidirectional context modeling, but their positional context differs fundament

Measurement Without Validity: The Compounding Reliability Problem in Agentic AI Evaluation

arXiv:2608.00794v2 Announce Type: replace Abstract: Agentic AI evaluation pipelines produce benchmark scores that justify deployment decisions, safety certifications, and regulatory compliance claims.

Tutorials

Measuring Explainer Stability via Attribution Separability

arXiv:2608.02697v1 Announce Type: cross Abstract: Attribution methods (AMs) assign an importance score to each feature and are widely adopted to explain black-box models. However, most methods can pro

tutorialsarxiv-cs-ai

Mechanism of Task-oriented Information Removal in In-context Learning

arXiv:2509.21012v4 Announce Type: replace-cross Abstract: In-context Learning (ICL) is an emerging few-shot learning paradigm based on modern Language Models (LMs), yet its inner mechanism remains unc

MemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale

arXiv:2608.02613v1 Announce Type: cross Abstract: Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models. Yet, existing memory bench

MeSS: City Mesh-Guided Outdoor Scene Generation with Cross-View Consistent Diffusion

arXiv:2508.15169v4 Announce Type: replace Abstract: Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual

safetyarxiv-cs-cv

Micro-Segmentation Anomaly Detection in Zero-Trust Software-Defined Network Fabrics

arXiv:2608.02627v1 Announce Type: cross Abstract: Zero Trust Architecture (ZTA) principles need rigorous network segmentation and ongoing verification to reduce implicit trust and lateral threat propa

applicationsarxiv-cs-cv

MIDI-LLM: Improving Text-to-MIDI Music Generation via Adapting Large Language Models

arXiv:2511.03942v2 Announce Type: replace-cross Abstract: We present MIDI-LLM, a recipe that improves multitrack text-to-MIDI generation via adapting Large Language Models (LLMs). MIDI-LLM expands an