Search: “concepts”

Stroke of Surprise: Progressive Semantic Illusions in Vector Sketching

arXiv:2602.12280v2 Announce Type: replace Abstract: Visual illusions traditionally rely on spatial manipulations such as multi-view consistency. In this work, we introduce Progressive Semantic Illusio

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Safety

The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

DGX agent

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

safetyarxiv-cs-ai

19 May 2026

Industry

Truth via Humor

This post likely discusses how humor can be an effective vehicle for communicating truth or revealing reality in ways that straightforward statements cannot. Musk may be commenting on how comedic fram

industryelon-musk--x

VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment

arXiv:2605.16775v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonan

Industry

'what do you think of blue ocean strategy?' 'i want a ocean so blue that it would be black like the night. nothing but open canvas and space…

David Holz expresses a poetic interpretation of Blue Ocean Strategy, describing a vision of unprecedented market space and opportunity so vast it appears almost limitless—using the metaphor of an ocea

industrydavid-holz--x

White-Box Sensitivity Auditing with Steering Vectors

arXiv:2601.16398v2 Announce Type: replace-cross Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of

safetyarxiv-cs-cl

Why Do Safety Guardrails Degrade Across Languages?

arXiv:2605.17173v1 Announce Type: cross Abstract: Large language models exhibit safety degradation in non-English languages. Standard evaluation relies on Jailbreak Success Rate (JSR), which confounds

Zero-Shot Faithful Textual Explanations via Directional-Derivative Influence on Predictions

model-releasesarxiv-cs-cv

arXiv:2605.16877v1 Announce Type: new Abstract: Zero-shot textual explanations aim to make image classifiers more transparent by probing their internal representations, without relying on task-specifi

AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression

arXiv:2605.15921v1 Announce Type: new Abstract: Object removal aims to eliminate specified objects from images while plausibly inpainting the affected regions with background content. Current training

An Introduction to Deep Reinforcement and Imitation Learning

arXiv:2512.08052v3 Announce Type: replace-cross Abstract: Embodied agents, such as robots and virtual characters, must continuously select actions to execute tasks effectively, solving complex sequent

safetyarxiv-cs-lg

Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas

arXiv:2605.15848v1 Announce Type: cross Abstract: Conversational interfaces powered by large language models (LLMs) are widely used for ideation and analysis, yet their linear structure limits explora

researcharxiv-cs-cl

Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation

arXiv:2605.15942v1 Announce Type: cross Abstract: Open-vocabulary segmentation models often struggle to generalize to unseen combinations of object categories and attributes, because fine-grained desc

DIPA: Distilled Preconditioned Algorithms for Solving Imaging Inverse Problems

arXiv:2605.15456v1 Announce Type: cross Abstract: Solving imaging inverse problems has usually been addressed by designing proper prior models of the underlying signal. However, minimizing the data fi

DiscussLLM: Teaching Large Language Models When to Speak

arXiv:2508.18167v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as

tutorialsarxiv-cs-cl

Entropic Auto-Encoding via Implicit Free-Energy Minimization

arXiv:2605.16164v1 Announce Type: new Abstract: Despite their ubiquity, variational autoencoders (VAEs) inherently suffer from posterior collapse, a failure mode in which latent variables are effectiv

researcharxiv-cs-lg

Multimodal Object Detection Under Sparse Forest-Canopy Occlusion

arXiv:2605.15326v1 Announce Type: new Abstract: Reliable detection of humans beneath forest canopy remains a difficult remote-sensing challenge due to sparse, structured, and viewpoint-dependent occlu

SAE-RNA: A Sparse Autoencoder Model for Interpreting RNA Language Model Representations

arXiv:2510.02734v2 Announce Type: replace-cross Abstract: Deep learning, particularly with the advancement of Large Language Models, has transformed biomolecular modeling, with protein language models

researcharxiv-cs-ai

Sampling-Based Global Optimal Control and Estimation via Semidefinite Programming

arXiv:2507.17572v3 Announce Type: replace Abstract: Global optimization has gained attraction over the past decades, thanks to the development of both theoretical foundations and efficient numerical r

researcharxiv-cs-ro

The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunities

arXiv:2506.14829v2 Announce Type: replace-cross Abstract: AI for Social Impact (AI4SI) is an emergent field harnessing interdisciplinarities between the fields of artificial intelligence (AI), machine

tutorialsarxiv-cs-ai

this would add some pretty granular feedback that doesn’t interrupt conversation flow, using a UI ppl are familiar with

This post likely discusses implementing non-intrusive feedback mechanisms in conversational AI systems that leverage familiar UI patterns to provide detailed user input without disrupting the natural

agentsyohei-nakajima--x

Often overlooked is the Frankfurt School’s central role, alongside French postmodernists, in forging Critical Theory and exporting it to Ame…

Often overlooked is the Frankfurt School’s central role, alongside French postmodernists, in forging Critical Theory and exporting it to America, where it evolved into one of the most influential (des

tutorialselon-musk--x

17 May 2026

We're still celebrating the moms who build, Mother's Day or not. Ruth is a designer who spent years making digital products without ever lea…

We're still celebrating the moms who build, Mother's Day or not. Ruth is a designer who spent years making digital products without ever learning to code. The moment Replit's AI agent landed in the ID

agentsreplit--x

16 May 2026

A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks

arXiv:2510.19973v4 Announce Type: replace-cross Abstract: The path to higher network autonomy in 6G lies beyond the mere optimization of key performance indicators (KPIs), requiring systems that perce

BOOKMARKS: Efficient Active Storyline Memory for Role-playing

arXiv:2605.14169v1 Announce Type: new Abstract: Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling)

researcharxiv-cs-cl

Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction

arXiv:2605.14569v1 Announce Type: new Abstract: Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neur

Causal Time Series Generation via Diffusion Models

arXiv:2509.20846v3 Announce Type: replace Abstract: Time series generation (TSG) synthesizes realistic sequences and has achieved remarkable success. Among TSG, conditional models generate sequences g

tutorialsarxiv-cs-lg

Compositional Video Generation via Inference-Time Guidance

arXiv:2605.14988v1 Announce Type: new Abstract: Text-to-video diffusion models generate realistic videos, but often fail on prompts requiring fine-grained compositional understanding, such as relation

Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning

arXiv:2508.01916v3 Announce Type: replace-cross Abstract: Understanding internal representations of neural models is a core interest of mechanistic interpretability. Due to its large dimensionality, t

researcharxiv-cs-ai

Exemplar Partitioning for Mechanistic Interpretability

model-releasesarxiv-cs-lg

arXiv:2605.14347v1 Announce Type: new Abstract: We introduce Exemplar Partitioning (EP), an unsupervised method for constructing interpretable feature dictionaries from large language model activation

Hardware

Falkor-IRAC: Graph-Constrained Generation for Verified Legal Reasoning in Indian Judicial AI

arXiv:2605.14665v1 Announce Type: new Abstract: Legal reasoning is not semantic similarity search. A court judgment encodes constrained symbolic reasoning: precedent propagation, procedural state tran

hardwarearxiv-cs-ai

GenExam: A Multidisciplinary Text-to-Image Exam

model-releasesarxiv-cs-cv

arXiv:2509.14232v5 Announce Type: replace Abstract: Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style bench

Kolmogorov-Arnold Chemical Reaction Neural Networks for learning pressure-dependent kinetic rate laws

model-releasesarxiv-cs-lg

arXiv:2511.07686v2 Announce Type: replace-cross Abstract: Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics direct

Metis AI: The Overlooked Middle Zone Between AI-Native and World-Movers

arXiv:2605.14407v1 Announce Type: new Abstract: The dominant discourse on AI limitations frames the boundary of AI capability as a divide between digital tasks (where AI excels) and physical tasks (wh

researcharxiv-cs-ai

On the Cultural Anachronism and Temporal Reasoning in Vision Language Models

arXiv:2605.15071v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly applied to cultural heritage materials, from digital archives to educational platforms. This work ident

Position: Behavioural Assurance Cannot Verify the Safety Claims Governance Now Demands

arXiv:2605.15164v1 Announce Type: cross Abstract: This position paper argues that behavioural assurance, even when carefully designed, is being asked to carry safety claims it cannot verify. AI govern

Prompt Segmentation and Annotation Optimisation: Controlling LLM Behaviour via Optimised Segment-Level Annotations

arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate

tutorialsarxiv-cs-ai

Hardware

Synthetic Sociality: How Generative Models Privatize the Social Fabric

arXiv:2605.14090v1 Announce Type: cross Abstract: We put forth a critical theoretical framework for analyzing generative models both descriptively and normatively. Our thesis is that generative models

hardwarearxiv-cs-lg

The Evaluation Trap: Benchmark Design as Theoretical Commitment

arXiv:2605.14167v1 Announce Type: new Abstract: Every AI benchmark operationalizes theoretical assumptions about the capability it claims to assess. When assumptions function as unexamined commitments

Training ML Models with Predictable Failures

arXiv:2605.15134v1 Announce Type: new Abstract: Estimating how often an ML model will fail at deployment scale is central to pre-deployment safety assessment, but a feasible evaluation set is rarely l

safetyarxiv-cs-lg

What Do EEG Foundation Models Capture from Human Brain Signals?

arXiv:2605.11410v2 Announce Type: replace Abstract: Clinical electroencephalogram (EEG) analysis rests on a hand-crafted feature catalog refined over decades, e.g., band power, connectivity, complexit

tutorialsarxiv-cs-ai

An Agentic LLM-Based Framework for Population-Scale Mental Health Screening

arXiv:2605.13046v1 Announce Type: new Abstract: Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from ele

agentsarxiv-cs-ai

Beyond Oversquashing: Understanding Signal Propagation in GNNs Via Observables

arXiv:2605.13383v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) perform computations on graphs by routing the signal between graph regions using a graph shift operator or a message passin

researcharxiv-cs-lg

Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with 'nonconform'

arXiv:2605.13642v1 Announce Type: cross Abstract: Most anomaly detection systems output scores rather than calibrated decisions, leaving practitioners to choose thresholds heuristically and without cl

tutorialsarxiv-cs-lg

Context-Aware Web Attack Detection in Open-Source SIEM Systems via MITRE ATT&CK-Enriched Behavioral Profiling

arXiv:2605.13337v1 Announce Type: cross Abstract: Security Information and Event Management (SIEM) systems aggregate log data from heterogeneous sources to detect coordinated attacks. Traditional rule

researcharxiv-cs-lg

Controlling Logical Collapse in LLMs via Algebraic Ontology Projection over F2

arXiv:2605.12968v1 Announce Type: cross Abstract: Do large language models internally encode ontological relations in a formally verifiable algebraic structure? We introduce Algebraic Ontology Project

Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems

arXiv:2605.13077v1 Announce Type: cross Abstract: Responsibility allocation -- determining the extent to which agents are accountable for outcomes -- is a fundamental challenge in the design and analy

Deep Learning as Neural Low-Degree Filtering: A Spectral Theory of Hierarchical Feature Learning

arXiv:2605.13612v1 Announce Type: new Abstract: Understanding how deep neural networks learn useful internal representations from data remains a central open problem in the theory of deep learning. We

tutorialsarxiv-cs-lg

Multi-Agent Systems in Emergency Departments: Validation Study on a ED Digital Twin

arXiv:2605.13345v1 Announce Type: new Abstract: Emergency departments (ED) face challenges in patient care and resource management. We propose to explore optimization strategies in a realistic and fle

agentsarxiv-cs-ai