Search: “context”

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models

arXiv:2605.09081v1 Announce Type: cross Abstract: We introduce the first universal pretraining corpus for industrial time-series data: FactoryNet. 51M datapoints across 23k end-to-end task executions

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Research

FERA: Uncertainty-Aware Federated Reasoning for Large Language Models

DGX agent

arXiv:2605.10082v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong reasoning capabilities when guided by high-quality demonstrations, yet such data is often distributed across

researcharxiv-cs-cl

12 May 2026

FinMoji: A Framework for Emoji-driven Sentiment Analysis in Financial Social Media

arXiv:2605.09469v1 Announce Type: new Abstract: This paper explores the use of emojis in financial sentiment analysis, focusing on the social media platform StockTwits. Emojis, increasingly prevalent

researcharxiv-cs-cl

Safety

Formal Policy Enforcement for Real-World Agentic Systems

arXiv:2602.16708v3 Announce Type: replace-cross Abstract: Security policy enforcement in contemporary agentic systems predominantly consists of embedding natural-language policies within an agent's sy

safetyarxiv-cs-ai

FRACTAL: SSM with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences

arXiv:2605.08833v1 Announce Type: new Abstract: Effective sequence modeling fundamentally requires balancing the retention of unbounded history with the high-resolution detection of abrupt short-term

From pre-training to downstream performance: Does domain-specific pre-training make sense?

arXiv:2605.08819v1 Announce Type: new Abstract: Deep learning techniques have revolutionised medical imaging, improving diagnostic accuracy and enabling both more accurate and earlier disease detectio

Tutorials

From Regression to Inference: Meta-Learning Predictors for Neural Architecture Search

arXiv:2605.09290v1 Announce Type: new Abstract: Prediction-based approaches are widely used in neural architecture search (NAS), where a predictor estimates the performance of candidate architectures

tutorialsarxiv-cs-lg

Local Ai

From Single-Step Edit Response to Multi-Step Molecular Optimization

arXiv:2605.10035v1 Announce Type: new Abstract: Conditional molecular optimization aims to edit a molecule to realize a specified property shift. In practice, structurally similar molecule data is sca

local-aiarxiv-cs-ai

Functional Subspace, where language models can use vector algebra to solve problems

arXiv:2602.01687v2 Announce Type: replace-cross Abstract: Large language models (LLMs) were invented for natural language tasks such as translation, but they have proved that they can perform highly c

General Agent Evaluation

arXiv:2602.22953v2 Announce Type: replace Abstract: General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measur

Generating Leakage-Free Benchmarks for Robust RAG Evaluation

arXiv:2605.08838v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is widely used to augment large language models (LLMs) with external knowledge. However, many benchmark datasets,

Geometry-aware Prototype Learning for Cross-domain Few-shot Medical Image Segmentation

arXiv:2605.10885v1 Announce Type: new Abstract: Cross-domain few-shot medical image segmentation (CD-FSMIS) requires a model to generalise simultaneously to novel anatomical categories and unseen imag

Geometry Guided Self-Consistency for Physical AI

arXiv:2605.08638v1 Announce Type: cross Abstract: State-of-the-art physical AI models generate a chunk of actions per inference through diffusion or flow matching, iteratively refining an initial nois

GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction

arXiv:2605.09973v1 Announce Type: cross Abstract: Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains

Safety

Good science starts with intellectual honesty, and I am not seeing it. I 100% believe the quote below and zero percent believe the seemingly…

Good science starts with intellectual honesty, and I am not seeing it. I 100% believe the quote below and zero percent believe the seemingly similar– but actually very different—quote that @geoffreyhi

safetygary-marcus--x

Agents

HAMLET: A Hierarchical and Adaptive Multi-Agent Framework for Live Embodied Theatrics

arXiv:2507.15518v5 Announce Type: replace Abstract: Creating an immersive and interactive theatrical experience is a long-term goal in the field of interactive narrative. The emergence of large langua

agentsarxiv-cs-ai

HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving

arXiv:2605.09972v1 Announce Type: cross Abstract: End-to-end autonomous driving has witnessed rapid progress, yet existing benchmarks are increasingly saturated, with state-of-the-art models achieving

Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning

arXiv:2605.09308v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) excel at relational reasoning but face two persistent challenges: the lack of interpretable attribution for heterogeneous

Human-Inspired Memory Architecture for LLM Agents

arXiv:2605.08538v1 Announce Type: new Abstract: Current LLM agents lack principled mechanisms for managing persistent memory across long interaction horizons. We present a biologically-grounded memory

Illusion-Aware Visual Preprocessing and Anti-Illusion Prompting for Classic Illusion Understanding in Vision-Language Models

arXiv:2605.08841v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit systematic bias toward visual illusions, recalling memorized facts rather than perceiving actual visual difference

Improved Mean Flows: On the Challenges of Fastforward Generative Models

arXiv:2512.02012v2 Announce Type: replace Abstract: MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key chal

Improving Generalization by Permutation Routing Across Model Copies

arXiv:2605.09256v1 Announce Type: cross Abstract: We introduce a use of the (M)-cover (or (M)-layer) transform for machine learning. The method replicates a model (M) times, but instead of coupling th

Infinite Mask Diffusion for Few-Step Distillation

arXiv:2605.10518v1 Announce Type: cross Abstract: Masked Diffusion Models (MDMs) have emerged as a promising alternative to autoregressive models in language modeling, offering the advantages of paral

Applications

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

applicationsarxiv-cs-ro

Tutorials

IntroLM: Introspective Language Models via Prefilling-Time Self-Evaluation

arXiv:2601.03511v2 Announce Type: replace-cross Abstract: A major challenge for the operation of large language models (LLMs) is how to predict whether a specific LLM will produce sufficiently high-qu

tutorialsarxiv-cs-ai

IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts

arXiv:2605.08664v1 Announce Type: new Abstract: Current image quality assessment methods are heavily biased towards global distortions (e.g., noise, blur), neglecting local perceptual artifacts such a

Agents

'It’s pretty easy to change models these days... what creates more lock-in is when state starts to accumulate behind these APIs... memory ha…

'It’s pretty easy to change models these days... what creates more lock-in is when state starts to accumulate behind these APIs... memory has a lot of gravity.' - @hwchase17, Co-Founder & CEO, @LangCh

agentsharrison-chase--x

JODA: Composable Joint Dynamics for Articulated Objects

arXiv:2605.09954v1 Announce Type: cross Abstract: Articulated objects used in simulation and embodied AI are typically specified by geometry and kinematic structure, but lack the fine-grained dynamica

Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation

arXiv:2601.11258v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) face the 'knowledge cutoff' challenge, where their frozen parametric memory prevents direct internalization of ne

Local Ai

LAGO: Language-Guided Adaptive Object-Region Focus for Zero-Shot Visual-Text Alignment

arXiv:2605.08156v1 Announce Type: cross Abstract: Zero-shot recognition aims to classify an image by selecting the most compatible label description from a set of candidate classes without any task-sp

local-aiarxiv-cs-ai

LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models

arXiv:2605.09806v1 Announce Type: cross Abstract: Large reasoning models, such as OpenAI o1 and DeepSeek-R1, tend to become increasingly verbose as their reasoning capabilities improve. These inflated

Applications

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling

arXiv:2605.10292v1 Announce Type: cross Abstract: Time series forecasting serves as an essential tool for many real-world applications, supporting tasks such as resource optimization and decision-maki

applicationsarxiv-cs-ai

Learning Graph Foundation Models on Riemannian Graph-of-Graphs

arXiv:2605.09993v1 Announce Type: new Abstract: Graph foundation models (GFMs), pretrained on massive graph data, have transformed graph machine learning by supporting general-purpose reasoning across

researcharxiv-cs-lg

Learning Multi-Indicator Weights for Data Selection: A Joint Task-Model Adaptation Framework with Efficient Proxies

arXiv:2605.09665v1 Announce Type: cross Abstract: Data selection is a key component of efficient instruction tuning for large language models, as recent work has shown that data quality often matters

Safety

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization

arXiv:2605.08978v1 Announce Type: new Abstract: Recent advancements in agentic test-time scaling allow models to gather environmental feedback before committing to final actions. A key limitation of e

safetyarxiv-cs-ai

Tutorials

Learning Unified Representations of Normalcy for Time Series Anomaly Detection

arXiv:2605.09685v1 Announce Type: cross Abstract: The core challenge in unsupervised anomaly detection is identifying abnormal patterns without prior knowledge of their characteristics. While existing

tutorialsarxiv-cs-ai

LLM Translation of Compiler Intermediate Representation

arXiv:2605.08247v1 Announce Type: cross Abstract: GCC and LLVM underpin much of modern software infrastructure, relying on distinct Intermediate Representations (IRs) to drive optimizations and code g

Loom: Hybrid Retrieval-Scoring Outfit Recommendation with Semantic Material Compatibility and Occasion-Aware Embedding Priors

arXiv:2605.09830v1 Announce Type: cross Abstract: We present Loom, an outfit recommendation system that combines neural embedding retrieval with structured domain scoring to generate complete, coheren

Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan

arXiv:2605.09156v1 Announce Type: cross Abstract: The diachronic evolution from Latin to the Romance languages involved a restructuring of the grammatical gender system from a tripartite configuration

MaD Physics: Evaluating information seeking under constraints in physical environments

arXiv:2605.10820v1 Announce Type: new Abstract: Scientific discovery is fundamentally a resource-constrained process that requires navigating complex trade-offs between the quality and quantity of mea

Agents

MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation

arXiv:2502.13451v5 Announce Type: replace Abstract: Vision-and-language navigation (VLN) is a key task in Embodied AI, requiring agents to navigate diverse and unseen environments while following natu

agentsarxiv-cs-ro

Measure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests

arXiv:2510.22170v2 Announce Type: replace Abstract: Persona conditioning is widely used to steer large language model (LLM) behavior, but it is unclear whether it induces stable behavioral structure o

MemQ: Integrating Q-Learning into Self-Evolving Memory Agents over Provenance DAGs

arXiv:2605.08374v1 Announce Type: new Abstract: Episodic memory allows LLM agents to accumulate and retrieve experience, but current methods treat each memory independently, i.e., evaluating retrieval

Meow-Omni 1: A Multimodal Large Language Model for Feline Ethology

model-releasesarxiv-cs-cl

arXiv:2605.09152v1 Announce Type: new Abstract: Deciphering animal intent is a fundamental challenge in computational ethology, largely because of semantic aliasing, the phenomenon where identical ext

MicroWorld: Empowering Multimodal Large Language Models to Bridge the Microscopic Domain Gap with Multimodal Attribute Graph

arXiv:2605.10120v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) show remarkable potential for scientific reasoning, yet their performance in specialized domains such as micr

Mixture of Layers with Hybrid Attention

arXiv:2605.09516v1 Announce Type: cross Abstract: Standard Mixture-of-Experts (MoE) transformers route tokens to expert subnetworks within each layer, but the layer structure itself remains monolithic

MPerS: Dynamic MLLM MixExperts Perception-Guided Remote Sensing Scene Segmentation

arXiv:2605.10769v1 Announce Type: cross Abstract: The multimodal fusion of images and scene captions has been extensively explored and applied in various fields. However, when dealing with complex rem

NaiAD: Initiate Data-Driven Research for LLM Advertising

arXiv:2605.09918v1 Announce Type: cross Abstract: Reconciling platform revenue with user experience in LLM advertising motivates a data-centric foundation. We introduce NaiAD, the first comprehensive