Search: “concepts”

Unsupervised Hierarchical Skill Discovery

arXiv:2601.23156v2 Announce Type: replace Abstract: We consider the problem of unsupervised skill segmentation and hierarchical structure discovery in reinforcement learning. While recent approaches h

29 May 2026

When and How Long? The Readout-Mediator Angle in Temporal Reasoning

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arXiv:2605.29126v1 Announce Type: cross Abstract: A linear probe can decode a representation almost perfectly and yet be completely irrelevant to how the model uses it. On calendar-date duration reaso

safetyarxiv-cs-ai

29 May 2026

Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization

arXiv:2605.28615v1 Announce Type: new Abstract: Despite the rapid progress of text-to-image (T2I) models, generating images that accurately reflect complex compositional prompts (covering attribute bi

safetyarxiv-cs-cv

DebFilter: Eradicating Biases Stashed in Value

arXiv:2605.28167v1 Announce Type: new Abstract: Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising proc

safetyarxiv-cs-cv

FEA-SLT: A Gloss-Free End-to-End Framework for Facial-Expression-Aware Sign Language Translation

arXiv:2601.03549v2 Announce Type: replace-cross Abstract: Sign Language Translation (SLT) is a challenging cross-modal task requiring joint modeling of manual articulations and non-manual signals. Exi

researcharxiv-cs-cl

HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling

arXiv:2512.23959v3 Announce Type: replace-cross Abstract: Multi-step retrieval-augmented generation (RAG) has become a widely adopted strategy for enhancing large language models (LLMs) on tasks that

Parameter-Efficient Generative Modeling with Controlled Vector Fields

model-releasesarxiv-cs-lg

arXiv:2605.28267v1 Announce Type: new Abstract: We introduce a continuous-time generative modeling framework, motivated by the Chow-Rashevskii theorem, that builds expressive flows from a small set of

Semi-Supervised Hypothesis Testing by Betting on Predictions

arXiv:2605.28533v1 Announce Type: new Abstract: We introduce a testing-by-betting framework that leverages predictions on unlabeled data to enhance the power of sequential hypothesis testing. Given li

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations

model-releasesarxiv-cs-lg

arXiv:2605.28149v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) extract interpretable features from Large Language Models, but standard variants enforce non-negativity, forcing separate lat

SuperValid: Capability-Aligned OOD Validation for Generalizable Downstream Scaling

model-releasesarxiv-cs-cl

arXiv:2605.28179v1 Announce Type: new Abstract: Scaling laws guide large language model training by relating compute to cross-entropy loss, and recent work further extends them to predict downstream b

The Attentional White Bear Effect in Transformer Language Models

arXiv:2605.28639v1 Announce Type: cross Abstract: Instruction-based suppression is widely used to prevent language models from generating prohibited content, yet it remains unclear whether suppression

The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation

arXiv:2601.17737v3 Announce Type: replace-cross Abstract: Recent advances in video generation have produced models capable of synthesizing stunning visual content from simple text prompts. However, th

Towards automated data analysis: A guided framework for LLM-based risk estimation

arXiv:2603.04631v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly integrated into critical decision-making pipelines, a trend that raises the demand for robust and auto

VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking

arXiv:2605.28083v1 Announce Type: new Abstract: While Vision-Language-Action (VLA) models have emerged as powerful generalist policies, their severe vulnerability to adversarial patches significantly

safetyarxiv-cs-cv

Which Pretraining Paradigm Better Serves Spatial Intelligence? An Empirical Comparison of Vision-Language and Video Generation Models

arXiv:2605.28132v1 Announce Type: new Abstract: Spatial intelligence requires visual representations that capture both semantic objects and geometric structure in the physical world. To support this,

tutorialsarxiv-cs-cv

AI Agent for Reverse-Engineering Legacy Finite-Difference Code and Translating to Devito

arXiv:2601.18381v2 Announce Type: replace Abstract: To facilitate the transformation of legacy finite difference implementations into the Devito environment, this study develops an integrated AI agent

Breaking the Epistemic Trap: Active Perception Under Compound Uncertainty

arXiv:2605.26627v1 Announce Type: cross Abstract: Deploying reinforcement learning in safety critical domains, from autonomous vehicles to medical decision support, is constrained by failures arising

safetyarxiv-cs-ro

Applications

Certified Causal Attribution for Real-Time Attack Forensics in 6G Network Slicing

arXiv:2605.26679v1 Announce Type: cross Abstract: Cross-slice attack attribution in 6G networks requires identifying causal propagation chains through shared infrastructure in under 100 ms. Existing m

applicationsarxiv-cs-ai

Confounder Detection via Treatment Intent: A New Observational Study Design

arXiv:2605.26413v1 Announce Type: cross Abstract: Understanding the effects of interventions is central to scientific progress, with randomized controlled trials (RCTs) regarded as the gold standard f

Cordyceps: Covert Control Attacks on LLMs via Data Poisoning

arXiv:2605.26595v1 Announce Type: cross Abstract: Large language models (LLMs) are often fine-tuned on uncurated text datasets that adversaries can poison. Existing poisoning attacks primarily rely on

Demystifying Video Reasoning

arXiv:2603.16870v2 Announce Type: replace-cross Abstract: Recent advances in video generation have revealed an unexpected phenomenon: diffusion-based video models exhibit non-trivial reasoning capabil

tutorialsarxiv-cs-ai

Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions

arXiv:2605.26256v1 Announce Type: new Abstract: Multimodal large language model (MLLM)-based embodied agents have shown strong potential for solving complex tasks in physical environments. However, pe

Qiskit QuantumKatas: Adapting Microsoft's Quantum Computing exercises for LLM evaluation

arXiv:2605.27210v1 Announce Type: cross Abstract: We adapt Microsoft's QuantumKatas -- a well-established quantum computing curriculum -- from Q# to Qiskit, the most widely-adopted quantum computing f

Towards Just-in-Time Adaptive Feedback: Enhancing Student Learning via Knowledge-Grounded LLM

arXiv:2605.26405v1 Announce Type: new Abstract: Educational interventions are effective tools for enhancing student learning. While Large Language Models (LLMs) allow for generating adaptive feedback

tutorialsarxiv-cs-cl

Towards Shared Embodied Intelligence in Humanoid Robots through Optimization Development and Testing of the Human Aware ergoCub Robot

arXiv:2605.26991v1 Announce Type: new Abstract: Collaboration is central to human behavior, enabling tasks beyond individual capability. This ability arises from coordinating actions through internal

researcharxiv-cs-ro

AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing

arXiv:2605.25358v1 Announce Type: cross Abstract: AI-associated lexical shifts have been documented mainly in Scientific English. We extend this work to 34 languages in the WMT News Crawl corpus, refi

BC Protocol: Structured Dual-Expert Dialogue for Eliciting High-Quality Chain-of-Thought Post-Training Data

arXiv:2605.25549v1 Announce Type: cross Abstract: High-quality expert chain-of-thought (CoT) data is one of the core bottlenecks in large language model (LLM) post-training. Existing data production m

CyBOKClaw: Human-in-the-Loop CyBOK Mapping for Cybersecurity Curriculum

arXiv:2605.24663v1 Announce Type: cross Abstract: This paper presents CyBOKClaw, an interpretable human-in-the-loop retrieval framework for mapping cybersecurity keywords or phrases (KWoPs) to the Cyb

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput

arXiv:2605.24632v1 Announce Type: cross Abstract: Recent demonstrations of large language models producing candidate and confirmed vulnerabilities in production software have renewed the narrative tha

tutorialsarxiv-cs-ai

Distinguishing Right from Wrong in Debates: Attribution Analysis of Chinese Harmful Memes

arXiv:2605.24344v1 Announce Type: new Abstract: Research on harmful meme detection has garnered significant attention, resulting in the development of numerous datasets and methods. However, progress

researcharxiv-cs-cl

ERNIE-Image Technical Report

model-releasesarxiv-cs-lg

arXiv:2605.25347v1 Announce Type: cross Abstract: We introduce ERNIE-Image, an open-source text-to-image generation model built upon an 8B single-stream DiT architecture. ERNIE-Image aims to bridge th

Fuzzy, Neutrosophic, and Uncertain Graph Theory: Properties and Applications

arXiv:2605.23936v1 Announce Type: new Abstract: This book presents a comprehensive and systematic survey of graph theory under uncertainty, with particular emphasis on the unifying role of the uncerta

Go witheFlow: Real-time Emotion Driven Audio Effects Modulation

arXiv:2510.02171v3 Announce Type: replace-cross Abstract: Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machin

Incorporating Deep Learning Design in Database Queries

arXiv:2605.24207v1 Announce Type: cross Abstract: Deep learning over relational databases is conventionally realized by translating data into graph representations and applying graph-based neural netw

Local Ai

Interpretation, Learning, and Empathy as One Constraint: A Residual-Adequacy Architecture with Accountable Abstention

arXiv:2605.24999v1 Announce Type: cross Abstract: An agent must act on the situation before it, learn what it cannot yet represent, and model other agents well enough to coordinate. These faculties ar

local-aiarxiv-cs-ai

Applications

Knowledge Graph Re-engineering Along the Ontological Continuum (extended version)

arXiv:2605.22093v2 Announce Type: replace Abstract: Knowledge graphs have become the primary vehicle for data integration and are critical to the success of modern AI, but the diversity of KG modellin

applicationsarxiv-cs-ai

Multi-market value-stacking: Battery control for combined imbalance participation and non-uniform FCR bidding

arXiv:2605.23964v1 Announce Type: cross Abstract: The growing share of Renewable Energy Sources (RES) in modern power systems increases both grid imbalances and frequency deviations, reinforcing the n

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting

arXiv:2605.25678v1 Announce Type: cross Abstract: We study the problem of multiclass PAC learning with bandit feedback in the realizable setting. In this framework, there is an unknown data distributi

PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding

model-releasesarxiv-cs-cl

arXiv:2602.01322v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) interpret neural network representations by decomposing activations into sparse combinations of dictionary atoms. H

Riemannian-Manifold Steering: Geometry-Aware Generative Autoencoders for Label-Free Steering

arXiv:2605.24942v1 Announce Type: cross Abstract: Steering a language model - intervening on its internal activations to change downstream behaviour - has recently expanded beyond linear interpolation

SAE-FD: Sparse Autoencoder Feature Distillation for Continual Learning of Large Language Models

arXiv:2605.25525v1 Announce Type: new Abstract: Continual learning enables large language models to adapt to evolving tasks without retraining from scratch, yet catastrophic forgetting remains a centr

Scaling Natural-Language Graph-Based Test Time Compute for Automated Theorem Proving

arXiv:2503.11657v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities in natural language processing tasks requiring multi-step logical reasoning capabili

researcharxiv-cs-cl

Toward Enactive Artificial Intelligence

arXiv:2605.24238v1 Announce Type: new Abstract: In this paper, we advocate for incorporating enactive approaches to perception and cognition into artificial intelligence (AI). Enactive approaches view

Towards end-to-end LLM-based censoring-aware survival analysis

arXiv:2605.25399v1 Announce Type: new Abstract: Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because ce

Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security

arXiv:2605.23989v1 Announce Type: new Abstract: Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks

Applications

Translators as Invisible Teachers of AI: Copyright, Translation Memory, and the Political Economy of Linguistic Data

arXiv:2605.24842v1 Announce Type: new Abstract: This paper examines how the labour of translators has been transformed into foundational data capital for the age of artificial intelligence (AI). Trans

applicationsarxiv-cs-cl

Why We Need World Models for AGI: Where LLMs Fail and How World Models May Outperform

arXiv:2605.23972v1 Announce Type: new Abstract: Large language models achieve strong performance in language generation and knowledge-intensive tasks, yet remain limited in settings requiring causal r

6G Communication Networks Enabling Embodied Agents: Architecture and Prototype

arXiv:2605.23263v1 Announce Type: cross Abstract: Embodied agents, which couple intelligent decision-making with physical actuation in the real world, impose far more stringent and heterogeneous commu