Search: “reasoning”

A Quantitative Definition of Intelligence

arXiv:2604.10873v1 Announce Type: new Abstract: We propose an operational, quantitative definition of intelligence for arbitrary physical systems. The intelligence density of a system is the ratio of

Tutorials

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models

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DGX agent

arXiv:2604.09921v1 Announce Type: new Abstract: Much work has been done on designing fast and accurate sampling for diffusion language models (dLLMs). However, these efforts have largely focused on th

tutorialsarxiv-cs-lg

14 Apr 2026

Tutorials

A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima

arXiv:2512.05534v4 Announce Type: replace-cross Abstract: As AI models achieve remarkable capabilities across diverse domains, understanding what representations they learn and how they encode concept

tutorialsarxiv-cs-ai

ADD for Multi-Bit Image Watermarking

arXiv:2604.11491v1 Announce Type: cross Abstract: As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promis

AI Integrity: A New Paradigm for Verifiable AI Governance

arXiv:2604.11065v1 Announce Type: new Abstract: AI systems increasingly shape high-stakes decisions in healthcare, law, defense, and education, yet existing governance paradigms -- AI Ethics, AI Safet

Hardware

AIRA_2: Overcoming Bottlenecks in AI Research Agents

arXiv:2603.26499v2 Announce Type: replace Abstract: Existing research has identified three structural performance bottlenecks in AI research agents: (1) synchronous single-GPU execution constrains sam

hardwarearxiv-cs-ai

ArtiCAD: Articulated CAD Assembly Design via Multi-Agent Code Generation

arXiv:2604.10992v1 Announce Type: new Abstract: Parametric Computer-Aided Design (CAD) of articulated assemblies is essential for product development, yet generating these multi-part, movable models f

agentsarxiv-cs-cv

Assessing Model-Agnostic XAI Methods against EU AI Act Explainability Requirements

arXiv:2604.09628v1 Announce Type: cross Abstract: Explainable AI (XAI) has evolved in response to expectations and regulations, such as the EU AI Act, which introduces regulatory requirements on AI-po

Assessing Privacy Preservation and Utility in Online Vision-Language Models

arXiv:2604.09695v1 Announce Type: cross Abstract: The increasing use of Online Vision Language Models (OVLMs) for processing images has introduced significant privacy risks, as individuals frequently

Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

arXiv:2604.10708v1 Announce Type: cross Abstract: Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typic

Beyond LLMs, Sparse Distributed Memory, and Neuromorphics <A Hyper-Dimensional SRAM-CAM 'VaCoAl' for Ultra-High Speed, Ultra-Low Power, and Low Cost>

arXiv:2604.11665v1 Announce Type: cross Abstract: This paper reports an unexpected finding: in a deterministic hyperdimensional computing (HDC) architecture based on Galois-field algebra, a path-depen

Beyond Monologue: Interactive Talking-Listening Avatar Generation with Conversational Audio Context-Aware Kernels

arXiv:2604.10367v1 Announce Type: new Abstract: Audio-driven human video generation has achieved remarkable success in monologue scenarios, largely driven by advancements in powerful video generation

Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation

arXiv:2604.09549v1 Announce Type: cross Abstract: Recommender systems are central to online services, enabling users to navigate through massive amounts of content across various domains. However, the

Beyond RAG for Cyber Threat Intelligence: A Systematic Evaluation of Graph-Based and Agentic Retrieval

arXiv:2604.11419v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) analysts must answer complex questions over large collections of narrative security reports. Retrieval-augmented generat

Beyond the Beep: Scalable Collision Anticipation and Real-Time Explainability with BADAS-2.0

model-releasesarxiv-cs-cl

arXiv:2604.05767v2 Announce Type: replace-cross Abstract: We present BADAS-2.0, the second generation of our collision anticipation system, building on BADAS-1.0, which showed that fine-tuning V-JEPA2

Bottleneck Tokens for Unified Multimodal Retrieval

arXiv:2604.11095v1 Announce Type: cross Abstract: Adapting decoder-only multimodal large language models (MLLMs) for unified multimodal retrieval faces two structural gaps. First, existing methods rel

Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?

model-releasesarxiv-cs-cv

arXiv:2511.21998v2 Announce Type: replace Abstract: Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance,

Tutorials

Can Small Training Runs Reliably Guide Data Curation? Rethinking Proxy-Model Practice

arXiv:2512.24503v2 Announce Type: replace-cross Abstract: Data teams at frontier AI companies routinely train small proxy models to make critical decisions about pretraining data recipes for full-scal

tutorialsarxiv-cs-ai

CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction

arXiv:2604.11202v1 Announce Type: cross Abstract: We present CapBench, a fully reproducible, multi-PDK dataset for capacitance extraction. The dataset is derived from open-source designs, including si

researcharxiv-cs-lg

Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation

arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas

researcharxiv-cs-cl

ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care

arXiv:2509.00891v3 Announce Type: replace Abstract: Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse

ChemPro: A Progressive Chemistry Benchmark for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult

Applications

CLASP: Closed-loop Asynchronous Spatial Perception for Open-vocabulary Desktop Object Grasping

arXiv:2604.11320v1 Announce Type: new Abstract: Robot grasping of desktop object is widely used in intelligent manufacturing, logistics, and agriculture.Although vision-language models (VLMs) show str

applicationsarxiv-cs-ro

Hardware

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts

arXiv:2604.10496v1 Announce Type: new Abstract: Outliers have emerged as a fundamental bottleneck in preserving accuracy for low-precision large models, particularly within Mixture-of-Experts (MoE) ar

hardwarearxiv-cs-lg

Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

arXiv:2604.10344v1 Announce Type: new Abstract: The classical approach to detecting depression from vision emphasizes interpretable features, such as facial expression, and classifiers such as the Sup

safetyarxiv-cs-cv

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision

arXiv:2604.10182v1 Announce Type: new Abstract: Current evaluations of autonomous coding agents assume an unrealistic, infinite-resource environment. However, real-world software engineering is a reso

DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis

arXiv:2604.01236v2 Announce Type: replace-cross Abstract: Traditional network architectures suffer from severe protocol ossification and structural fragility due to their reliance on static, human-def

DecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

arXiv:2503.11892v3 Announce Type: replace Abstract: Multimodal representation learning aims to capture both shared and complementary semantic information across multiple modalities. However, the intri

safetyarxiv-cs-cv

Decoding Ancient Oracle Bone Script via Generative Dictionary Retrieval

arXiv:2604.09668v1 Announce Type: cross Abstract: Understanding humanity's earliest writing systems is crucial for reconstructing civilization's origins, yet many ancient scripts remain undeciphered.

researcharxiv-cs-cv

Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game

arXiv:2604.10717v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, yet introduce a critical security vulnerability: R

Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent Debate

arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote

safetyarxiv-cs-cl

Applications

DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation

arXiv:2507.13292v3 Announce Type: replace Abstract: Accurate age verification can protect underage users from unauthorized access to online platforms and e-commerce sites that provide age-restricted s

applicationsarxiv-cs-cv

Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction

arXiv:2604.10786v1 Announce Type: cross Abstract: Narrative understanding requires multidimensional semantic structures. This study investigates whether BERT embeddings encode dimensions of fictional

Applications

Dual-Margin Embedding for Fine-Grained Long-Tailed Plant Taxonomy

arXiv:2512.18994v2 Announce Type: replace Abstract: Taxonomic classification of ecological families, genera, and species underpins biodiversity monitoring and conservation. Existing computer vision me

applicationsarxiv-cs-cv

Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models

arXiv:2604.10567v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to autoregressive language models, offering the potential for parallel

Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech

arXiv:2604.11417v1 Announce Type: cross Abstract: Co-speech gestures increase engagement and improve speech understanding. Most data-driven robot systems generate rhythmic beat-like motion, yet few in

End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answering

arXiv:2511.09282v3 Announce Type: replace-cross Abstract: Significant progress has been made in spoken question answering (SQA) in recent years. However, many existing methods, including large audio l

safetyarxiv-cs-cl

Local Ai

Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention

arXiv:2512.11811v3 Announce Type: replace-cross Abstract: Crowdsourced social media imagery provides real-time visual evidence of urban flooding but often lacks reliable geographic metadata for emerge

local-aiarxiv-cs-ai

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

arXiv:2604.11462v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle with long-horizon tasks due to the 'context bottleneck' and the 'lost-in-the-middle' phenomenon, where accumulated

Evaluating Cooperation in LLM Social Groups through Elected Leadership

arXiv:2604.11721v1 Announce Type: cross Abstract: Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. Wh

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE

arXiv:2603.06003v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) language models achieve strong capability at low per-token compute, yet deployment remains constrained by memory fo

researcharxiv-cs-lg

Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs

arXiv:2602.01064v2 Announce Type: replace Abstract: Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more eff

researcharxiv-cs-cl

Factorizing formal contexts from closures of necessity operators

arXiv:2604.09582v1 Announce Type: new Abstract: Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factori

FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views

arXiv:2604.09862v1 Announce Type: new Abstract: Recent advances in vision foundation models have revolutionized geometry reconstruction and semantic understanding. Yet, most of the existing approaches

researcharxiv-cs-cv

FGML-DG: Feynman-Inspired Cognitive Science Paradigm for Cross-Domain Medical Image Segmentation

arXiv:2604.10524v1 Announce Type: new Abstract: In medical image segmentation across multiple modalities (e.g., MRI, CT, etc.) and heterogeneous data sources (e.g., different hospitals and devices), D

safetyarxiv-cs-cv

FlashMem: Distilling Intrinsic Latent Memory via Computation Reuse

model-releasesarxiv-cs-cl

arXiv:2601.05505v2 Announce Type: replace Abstract: The stateless architecture of Large Language Models inherently lacks the mechanism to preserve dynamic context, compelling agents to redundantly rep

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments

arXiv:2603.23964v2 Announce Type: replace Abstract: The remarkable progress of reinforcement learning (RL) is intrinsically tied to the environments used to train and evaluate artificial agents. Movin