Search: “context”

Can Large Language Models Detect Methodological Flaws? Evidence from Gesture Recognition for UAV-Based Rescue Operation Based on Deep Learning

arXiv:2604.14161v1 Announce Type: new Abstract: Reliable evaluation is essential in machine learning research, yet methodological flaws-particularly data leakage-continue to undermine the validity of

applicationsarxiv-cs-cl

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CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

DGX agent

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

model-releasesarxiv-cs-cl

17 Apr 2026

ClimateCause: Complex and Implicit Causal Structures in Climate Reports

arXiv:2604.14856v1 Announce Type: new Abstract: Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, di

connect, ingest, extract, enrich

This post likely discusses a four-step framework for data processing and AI workflows: connecting to data sources, ingesting raw data, extracting relevant information, and enriching it with additional

agentsyohei-nakajima--x

DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answering

arXiv:2604.15140v1 Announce Type: new Abstract: We introduce DiscoTrace, a method to identify the rhetorical strategies that answerers use when responding to information-seeking questions. DiscoTrace

tutorialsarxiv-cs-cl

Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design

arXiv:2512.24120v2 Announce Type: replace Abstract: Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints requir

researcharxiv-cs-cv

Expert-Guided Class-Conditional Goodness-of-Fit Scores for Interpretable Classification with Informative Missingness: An Application to Seismic Monitoring

arXiv:2604.14809v1 Announce Type: cross Abstract: We study a classification problem with three key challenges: pervasive informative missingness, the integration of partial prior expert knowledge into

Expressivity of Transformers: A Tropical Geometry Perspective

arXiv:2604.14727v1 Announce Type: new Abstract: To quantify the geometric expressivity of transformers, we introduce a tropical geometry framework to characterize their exact spatial partitioning capa

Fastest way to deploy deepagents gets even more powerful

applicationsharrison-chase--x

Fastest way to deploy deepagents gets even more powerful we just shipped support for subagents with `deepagents deploy`! add an agents/ dir to your project with an AGENTS.md per specialized subagent.

Federated Multi-Task Clustering

arXiv:2512.22897v3 Announce Type: replace Abstract: Spectral clustering has emerged as one of the most effective clustering algorithms due to its superior performance. However, most existing models ar

Formal Architecture Descriptors as Navigation Primitives for AI Coding Agents

model-releasesarxiv-cs-ai

arXiv:2604.13108v1 Announce Type: cross Abstract: AI coding agents spend a substantial fraction of their tool calls on undirected codebase exploration. We investigate whether providing agents with for

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step

safetyarxiv-cs-ai

Hardware

Friends, housemates, officemates. Maybe lovers?

This post likely explores the various relationship dynamics and social connections people develop in shared living and working spaces, with a speculative or humorous tone suggested by the 'Maybe lover

hardwaredylan-patel--x

Hardware

From Natural Language to PromQL: A Catalog-Driven Framework with Dynamic Temporal Resolution for Cloud-Native Observability

arXiv:2604.13048v1 Announce Type: cross Abstract: Modern cloud-native platforms expose thousands of time series metrics through systems like Prometheus, yet formulating correct queries in domain-speci

hardwarearxiv-cs-ai

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi

researcharxiv-cs-cl

Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI

arXiv:2403.10559v3 Announce Type: replace Abstract: This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing

safetyarxiv-cs-lg

Grok 4.3 Beta is insanely good and now comes with powerful new tools that are super helpful for everyday use: • Create clean slides, graphs,…

Grok 4.3 Beta is insanely good and now comes with powerful new tools that are super helpful for everyday use: • Create clean slides, graphs, images and dashboards • Pull real-time data and images dire

applicationselon-musk--x

Hoi! -- A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation

arXiv:2512.04884v3 Announce Type: replace Abstract: We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during rea

researcharxiv-cs-ro

Hybrid Decision Making via Conformal VLM-generated Guidance

arXiv:2604.14980v1 Announce Type: cross Abstract: Building on recent advances in AI, hybrid decision making (HDM) holds the promise of improving human decision quality and reducing cognitive load. We

tutorialsarxiv-cs-cl

Identifying Information from Observations with Uncertainty and Novelty

arXiv:2501.09331v3 Announce Type: replace Abstract: A machine that learns a task from observations must encounter and process uncertainty and novelty, especially when it is to maintain performance whe

Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends

arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as

applicationsarxiv-cs-ai

Learning temporal embeddings from electronic health records of chronic kidney disease patients

arXiv:2601.18675v2 Announce Type: replace Abstract: We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations w

MEBench: A Novel Benchmark for Understanding Mutual Exclusivity Bias in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2505.20122v2 Announce Type: replace Abstract: This paper introduces MEBench, a novel benchmark for evaluating mutual exclusivity (ME) bias, a cognitive phenomenon observed in children during wor

Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation

arXiv:2604.15190v1 Announce Type: cross Abstract: Simulating group-level user behavior enables scalable counterfactual evaluation of merchant strategies without costly online experiments. However, bui

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation

arXiv:2604.15101v1 Announce Type: cross Abstract: Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents bas

applicationsarxiv-cs-lg

MinShap: A Modified Shapley Value Approach for Feature Selection

arXiv:2604.15107v1 Announce Type: cross Abstract: Feature selection is a classical problem in statistics and machine learning, and it continues to remain an extremely challenging problem especially in

Multigrain-aware Semantic Prototype Scanning and Tri-Token Prompt Learning Embraced High-Order RWKV for Pan-Sharpening

model-releasesarxiv-cs-cv

arXiv:2604.14622v1 Announce Type: new Abstract: In this work, we propose a Multigrain-aware Semantic Prototype Scanning paradigm for pan-sharpening, built upon a high-order RWKV architecture and a tri

Non-intrusive Learning of Physics-Informed Spatio-temporal Surrogate for Accelerating Design

arXiv:2604.14424v1 Announce Type: new Abstract: Most practical engineering design problems involve nonlinear spatio-temporal dynamical systems. Multi-physics simulations are often performed to capture

Optimal algorithmic complexity of inference in quantum kernel methods

arXiv:2604.15214v1 Announce Type: cross Abstract: Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised learning. A key bottleneck is the cost of infere

Optimizing the Network Topology of a Linear Reservoir Computer

arXiv:2509.23391v3 Announce Type: replace-cross Abstract: Machine learning has become a fundamental approach for modeling, prediction, and control, enabling systems to learn from data and perform comp

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games

model-releasesarxiv-cs-ai

arXiv:2506.03610v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are reshaping the game industry, by enabling more intelligent and human-preferable characters. Yet, current game b

OVT-MLCS: An Online Visual Tool for MLCS Mining from Long or Big Sequences

arXiv:2604.13037v1 Announce Type: cross Abstract: Mining multiple longest common subsequences (extit{MLCS}) from a set of sequences of three or more over a finite alphabet Sigma (a classical NP-hard p

researcharxiv-cs-ai

POP: Prefill-Only Pruning for Efficient Large Model Inference

model-releasesarxiv-cs-cl

arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation

arXiv:2603.13683v2 Announce Type: replace Abstract: Although debiased large language models (LLMs) excel at handling known or low-bias prompts, they often fail on unfamiliar and high-bias prompts. We

Psychological Steering of Large Language Models

arXiv:2604.14463v1 Announce Type: new Abstract: Large language models (LLMs) emulate a consistent human-like behavior that can be shaped through activation-level interventions. This paradigm is conver

researcharxiv-cs-cl

Quantitative Approximation Rates for Group Equivariant Learning

arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx

Safe Reinforcement Learning using Action Projection: Safeguard the Policy or the Environment?

arXiv:2509.12833v2 Announce Type: replace Abstract: Projection-based safety filters, which modify unsafe actions by mapping them to the closest safe alternative, are widely used to enforce safety cons

safetyarxiv-cs-lg

SciFi: A Safe, Lightweight, User-Friendly, and Fully Autonomous Agentic AI Workflow for Scientific Applications

arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab

agentsarxiv-cs-ai

Segment-Level Coherence for Robust Harmful Intent Probing in LLMs

arXiv:2604.14865v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and Nucl

researcharxiv-cs-cl

Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go?

arXiv:2604.13826v1 Announce Type: cross Abstract: Sentiment analysis in software engineering focuses on understanding emotions expressed in software artifacts. Previous research highlighted the limita

researcharxiv-cs-ai

SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing

arXiv:2604.14399v1 Announce Type: new Abstract: Autonomous on-orbit servicing demands embodied agents that perceive through visual sensors, reason about 3D spatial situations, and execute multi-phase

agentsarxiv-cs-ro

Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects

arXiv:2510.07890v3 Announce Type: replace Abstract: Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are pri

applicationsarxiv-cs-cl

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

'The post all LLMs hate and want you to NOT SEE' ^^ Serious title, you can also discuss this with the LLM, it would be biased against it, as…

'The post all LLMs hate and want you to NOT SEE' ^^ Serious title, you can also discuss this with the LLM, it would be biased against it, as it's known at this point that memory is the true long term

agentsharrison-chase--x

The Specification Trap: Why Static Value Alignment Alone Is Insufficient for Robust Alignment

arXiv:2512.03048v4 Announce Type: replace-cross Abstract: Static content-based AI value alignment is insufficient for robust alignment under capability scaling, distributional shift, and increasing au

safetyarxiv-cs-lg

Theory of Mind in Action: The Instruction Inference Task in Dynamic Human-Agent Collaboration

model-releasesarxiv-cs-cl

arXiv:2507.02935v2 Announce Type: replace Abstract: Successful human-agent teaming relies on an agent being able to understand instructions given by a (human) principal. In many cases, an instruction

This feature is powered by Replit’s parallel agents, introduced in Agent 4. Replit can spin up separate copies of your project, work on them…

This feature is powered by Replit’s parallel agents, introduced in Agent 4. Replit can spin up separate copies of your project, work on them in parallel, and then combine the results at the end- handl

agentsreplit--x

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback

model-releasesarxiv-cs-lg

arXiv:2507.15066v5 Announce Type: replace Abstract: Time series anomaly detection (TSAD) has traditionally focused on binary classification and often lacks the fine-grained categorization and explanat