Search: “concepts”

arXiv:2604.14398v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) are a promising propulsion concept that may offer higher thermodynamic efficiency and specific impulse than convent

agentsarxiv-cs-lg

17 Apr 2026

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VisRet: Visualization Improves Knowledge-Intensive Text-to-Image Retrieval

DGX agent

arXiv:2505.20291v4 Announce Type: replace-cross Abstract: Text-to-image retrieval (T2I retrieval) remains challenging because cross-modal embeddings often behave as bags of concepts, underrepresenting

model-releasesarxiv-cs-cl

17 Apr 2026

Local Ai

Evaluating Language Models for Harmful Manipulation

arXiv:2603.25326v4 Announce Type: replace Abstract: Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a f

local-aiarxiv-cs-ai

15 Apr 2026

WiseOWL: A Methodology for Evaluating Ontological Descriptiveness and Semantic Correctness for Ontology Reuse and Ontology Recommendations

arXiv:2604.12025v1 Announce Type: new Abstract: The Semantic Web standardizes concept meaning for humans and machines, enabling machine-operable content and consistent interpretation that improves adv

15 Apr 2026

CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification

arXiv:2604.01687v2 Announce Type: replace Abstract: Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address. A tool

Efficient Personalization of Generative User Interfaces

arXiv:2604.09876v1 Announce Type: cross Abstract: Generative user interfaces (UIs) create new opportunities to adapt interfaces to individual users on demand, but personalization remains difficult bec

Graph Retention Networks for Dynamic Graphs

arXiv:2411.11259v3 Announce Type: replace Abstract: In this paper, we propose Graph Retention Networks (GRNs) as a unified architecture for deep learning on dynamic graphs. The GRN extends the concept

Tutorials

KL Divergence Between Gaussians: A Step-by-Step Derivation for the Variational Autoencoder Objective

arXiv:2604.11744v1 Announce Type: new Abstract: Kullback-Leibler (KL) divergence is a fundamental concept in information theory that quantifies the discrepancy between two probability distributions. I

tutorialsarxiv-cs-lg

Prompt Relay: Inference-Time Temporal Control for Multi-Event Video Generation

arXiv:2604.10030v1 Announce Type: new Abstract: Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal suc

Quantitative Introspection in Language Models: Tracking Emotive States Across Conversation

arXiv:2603.18893v2 Announce Type: replace Abstract: Tracking the internal states of large language models across conversations is important for safety, interpretability, and model welfare, yet current

RUMLEM: A Dictionary-Based Lemmatizer for Romansh

arXiv:2604.11233v1 Announce Type: new Abstract: Lemmatization -- the task of mapping an inflected word form to its dictionary form -- is a crucial component of many NLP applications. In this paper, we

Tutorials

Specificity-aware reinforcement learning for fine-grained open-world classification

arXiv:2603.03197v3 Announce Type: replace Abstract: Classifying fine-grained visual concepts under open-world settings, i.e., without a predefined label set, demands models to be both accurate and spe

tutorialsarxiv-cs-cv

A Benchmark of Dexterity for Anthropomorphic Robotic Hands

model-releasesarxiv-cs-ro

arXiv:2604.09294v1 Announce Type: new Abstract: Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often use

13 Apr 2026

ClusterMark: Towards Robust Watermarking for Autoregressive Image Generators with Visual Token Clustering

arXiv:2508.06656v2 Announce Type: replace Abstract: In-generation watermarking for latent diffusion models has recently shown high robustness in marking generated images for easier detection and attri

13 Apr 2026

Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis

arXiv:2604.08809v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) represent visual content as structured, editable code. Each element (path, shape, or text node) can be individually inspe

researcharxiv-cs-lg

13 Apr 2026

Active Statistical Inference

arXiv:2403.03208v3 Announce Type: replace-cross Abstract: Inspired by the concept of active learning, we propose active inferencenicode{x2013}a methodology for statistical inference with machine-l

researcharxiv-cs-lg

Floating or Suggesting Ideas? A Large-Scale Contrastive Analysis of Metaphorical and Literal Verb-Object Constructions

arXiv:2604.08275v1 Announce Type: new Abstract: Metaphor pervades everyday language, allowing speakers to express abstract concepts via concrete domains. While prior work has studied metaphors cogniti

From Ground Truth to Measurement: A Statistical Framework for Human Labeling

arXiv:2604.07591v1 Announce Type: cross Abstract: Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human

Implantable Adaptive Cells: A Novel Enhancement for Pre-Trained U-Nets in Medical Image Segmentation

arXiv:2405.03420v2 Announce Type: cross Abstract: This paper introduces a novel approach to enhance the performance of pre-trained neural networks in medical image segmentation using gradient-based Ne

Mixed-Initiative Context: Structuring and Managing Context for Human-AI Collaboration

arXiv:2604.07121v1 Announce Type: cross Abstract: In the human-AI collaboration area, the context formed naturally through multi-turn interactions is typically flattened into a chronological sequence

A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods

arXiv:2608.10203v1 Announce Type: new Abstract: Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibi

12 Aug 2026

Logit Lens Supervision for Patch-Level Explanations in Vision-Language Models

arXiv:2602.01530v2 Announce Type: replace Abstract: Modern autoregressive Vision-Language Models (VLMs) can generate fluent answers while their visual-token representations become weakly tied to the i

researcharxiv-cs-cv

12 Aug 2026

Toward a Theory of Value in AI Alignment

arXiv:2608.10327v1 Announce Type: new Abstract: Can AI systems be aligned to human values? The popularization of large language models (LLMs) and multi-modal foundation models has seen a rise in harms

12 Aug 2026

From Rebound to Remedy: Understanding and Mitigating Reward Hacking via Representation Engineering

arXiv:2604.01476v2 Announce Type: replace-cross Abstract: Reinforcement learning for LLMs is vulnerable to reward hacking, where models exploit shortcuts to maximize reward without solving the intende

Applications

Human-Guided Causal Knowledge Injection for Virtual Cells

arXiv:2608.08430v1 Announce Type: cross Abstract: Virtual cells employ machine learning models to simulate and predict cellular behaviors, serving as a critical computational framework for investigati

applicationsarxiv-cs-ai

The Voiceprint Fallacy: Why Voices Are Not Unique Biometric Imprints

arXiv:2608.07980v1 Announce Type: cross Abstract: In recent years, the term voiceprint has regained attention, particularly in technological applications and policy-making contexts, often carrying the

Wisdom in Unity: The Role of Multilingual Training in Figurative Language Identification in Proverbs

arXiv:2608.08090v1 Announce Type: new Abstract: Although multilingual approaches to figurative language identification are not new, the shift beyond language homogeneous training data requires a clear

CASA: Classification Augmented with Safety Attention for Robust Multimodal Alignment

arXiv:2604.00310v2 Announce Type: replace-cross Abstract: Multimodal large-language models (MLLMs) often experience degraded safety alignment when harmful queries exploit cross-modal interactions. Mod

Evaluating Useful Surrogate Models for Configuration Tuning Beyond Accuracy: A Fitness Landscape Analysis Perspective

arXiv:2509.21945v2 Announce Type: replace-cross Abstract: To efficiently tune configuration for better software system performance (e.g., latency) at the deployment and maintenance stage, many tuners

Hidden Gauge Controls Feature Specialization in ReLU Networks

arXiv:2608.06766v1 Announce Type: cross Abstract: Training changes a network's predictions while allocating task-relevant structure across its internal units. In an overparameterized ReLU network, sev

InsertFuse: A Unified Framework for Multi-Category Reference-Guided Image Insertion

model-releasesarxiv-cs-cv

arXiv:2608.06490v1 Announce Type: new Abstract: We present InsertFuse, a unified framework for multi-category reference-guided image insertion. Its key idea is to decouple category-specific expertise

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv:2509.16462v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used in high-stakes decision-making systems, where biased predictions can reinforce social and economi

Challenges in Evaluating Explanation Methods for Static and Evolving Data

arXiv:2608.06351v1 Announce Type: new Abstract: This paper addresses the limitations of Explainable Artificial Intelligence (XAI) with respect to insufficient evaluation. They are illustrated through

7 Aug 2026

Local Ai

Bi-Level Reinforcement Learning Pathway for Sim-to-Real Optimality

arXiv:2510.17709v2 Announce Type: replace-cross Abstract: Training Reinforcement Learning (RL) policies using simulation models before deployment in real-world environments is a common strategy when r

local-aiarxiv-cs-ai

6 Aug 2026

One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP

arXiv:2505.19840v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) have achieved widespread success yet remain prone to adversarial attacks. Typically, such attacks either involve f

6 Aug 2026

BAP-SQL: Budget-Aware Observation Planning for Agentic Text-to-SQL

arXiv:2608.02876v1 Announce Type: new Abstract: Tool-using agents do not merely consume observations: their actions determine what arrives next. In agentic text-to-SQL, a broad query can spend context

Disentangling MLP Neuron Weights in Vocabulary Space

model-releasesarxiv-cs-cl

arXiv:2604.06005v2 Announce Type: replace Abstract: Interpreting the information encoded in language model weights remains a fundamental challenge in mechanistic interpretability. In this work, we int

NOMADD: Numerical Optimization of Models Adapting to Data Drift

arXiv:2608.02845v1 Announce Type: new Abstract: Tabular model performance degrades when feature distributions change over time or the relationship between features and outcome variables change over ti

Perceptual Anchoring: Prototype-Guided Text Calibration for Training-free Open-Vocabulary Semantic Segmentation

arXiv:2608.03991v1 Announce Type: new Abstract: Training-free open-vocabulary semantic segmentation (OVSS) partitions an image into semantically distinct regions based on arbitrary text descriptions,

Toward Visual Grounding: A Survey

arXiv:2412.20206v4 Announce Type: replace Abstract: Visual Grounding, also known as Referring Expression Comprehension and Phrase Grounding, aims to ground the specific region(s) within the image(s) b

researcharxiv-cs-cv

Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions

model-releasesarxiv-cs-cl

arXiv:2602.05220v4 Announce Type: replace Abstract: Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

arXiv:2608.01968v1 Announce Type: new Abstract: Transformer models are most often understood through what they do: their benchmark performance, generation quality, or behavior on downstream tasks. Yet

DS@GT ARC at MEDIQA-CORE-Task-1 2026: Trimodal Model Fusion with Task-Specific Gates for Brain Tumor Subtype Classification

model-releasesarxiv-cs-cv

arXiv:2608.00086v1 Announce Type: new Abstract: Brain tumor diagnosis is a time-sensitive process in which patients may wait weeks for a finalized pathology report. This problem motivates automated sy

Learning to See Locally and Align Clinically with Pathology Semantics for Radiology Report Generation

arXiv:2608.00279v1 Announce Type: cross Abstract: Recent radiology-adapted vision-language models have achieved strong performance on standard report generation benchmarks, yet their robustness and ge

Neural Circuit Function Inference with LLMs

arXiv:2608.00059v1 Announce Type: new Abstract: The success of connectome mapping now shifts the challenge of understanding the nervous system to the interpretation of neural circuits. Here, we devise

When Words Divide: Diachronic Ideological Polarization in Political Discourse on Social Media

arXiv:2608.01176v1 Announce Type: new Abstract: Political polarization has become a defining feature of online discourse, yet its long-term evolution remains poorly understood. We present a longitudin

Applications

CalibratedRubric: Task-Adaptive Rubric Banks for Open-Ended LLM Evaluation

arXiv:2607.29252v1 Announce Type: cross Abstract: Reliable evaluation of open-ended LLM outputs requires fine-grained rubrics, yet expert curation is costly and difficult to scale. Existing automated

applicationsarxiv-cs-ai

3 Aug 2026

COntExt: Towards Context-Aware Ontology Extension from Operational Metrics

arXiv:2607.29553v1 Announce Type: new Abstract: Organizations increasingly define operational metrics in structured, machine-readable formats to monitor systems, processes, and compliance. These metri