All entries

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

DGX agent

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

5 Aug 2026

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

Let's create with Qwen-Image-3.0-Pro on fal! 🎨

Let's create with Qwen-Image-3.0-Pro on fal! 🎨 Qwen Image 3.0 Pro is now available on fal - Renders complex, dense typography - Preserves key details like facial features and identity while applying c

model-releasesqwen--x

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

LFM2.5-2.6B on a OnePlus 13 at 17 tok/s ~ Pure CPU

model-releasesr-localllama

As you all know the model is 2.69B parameters with a 128K context window and purpose-built for multi-step agent workflows. What you are seeing is the Q4_K_M GGUF running on my own inference engine bui

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

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

model-releasesarxiv-cs-cl

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

model-releasesarxiv-cs-cl

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

Love the latest string of releases and the moves that the Langchain team has been making. Langchain's React implementation was the the first…

Love the latest string of releases and the moves that the Langchain team has been making. Langchain's React implementation was the the first ever agent i built though their framework couldn't compete

agentsharrison-chase--x

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

model-releasesarxiv-cs-cl

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

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

Meta is offering a cheaper Muse Spark 1.2 'contributor' tier priced at 0.10/1M input and 0.20/1M output tokens in exchange for using user prompts for training (Wall Street Journal)

Wall Street Journal: Meta is offering a cheaper Muse Spark 1.2 “contributor” tier priced at 0.10/1M input and 0.20/1M output tokens in exchange for using user prompts for training — The company, press

agentstechmeme

Meta releases Muse Code in beta, a terminal coding agent powered by Muse Spark 1.2, a coding-focused model priced at 1.25/1M input and 4.25/1M output tokens (Jonathan Vanian/CNBC)

Jonathan Vanian / CNBC: Meta releases Muse Code in beta, a terminal coding agent powered by Muse Spark 1.2, a coding-focused model priced at 1.25/1M input and 4.25/1M output tokens — Meta is rolling o

agentstechmeme

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