Search: “reasoning”

Identity-Decoupled Anonymization for Visual Evidence in Multi-modal Retrieval-Augmented Generation

arXiv:2604.23584v1 Announce Type: new Abstract: Multi-modal retrieval-augmented generation (MRAG) systems retrieve visual evidence from large image corpora to ground the responses of large multi-modal

researcharxiv-cs-cv

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IndustryAssetEQA: A Neurosymbolic Operational Intelligence System for Embodied Question Answering in Industrial Asset Maintenance

DGX agent

arXiv:2604.23446v1 Announce Type: new Abstract: Industrial maintenance environments increasingly rely on AI systems to assist operators in understanding asset behavior, diagnosing failures, and evalua

safetyarxiv-cs-ai

28 Apr 2026

Learning Evidence of Depression Symptoms via Prompt Induction

arXiv:2604.24376v1 Announce Type: new Abstract: Depression places substantial pressure on mental health services, and many people describe their experiences outside clinical settings in high-volume us

LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models

arXiv:2604.23950v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have recently demonstrated remarkable capabilities in visual understanding and reasoning, but they also impose significant

safetyarxiv-cs-cv

MarketBench: Evaluating AI Agents as Market Participants

model-releasesarxiv-cs-ai

arXiv:2604.23897v1 Announce Type: new Abstract: Markets are a promising way to coordinate AI agent activity for similar reasons to those used to justify markets more broadly. In order to effectively p

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment

arXiv:2604.24178v1 Announce Type: cross Abstract: Multi-Objective Alignment aims to align Large Language Models (LLMs) with diverse and often conflicting human values by optimizing multiple objectives

MindTrellis: Co-Creating Knowledge Structures with AI through Interactive Visual Exploration

arXiv:2604.23129v1 Announce Type: cross Abstract: Knowledge workers face increasing challenges in synthesizing information from multiple documents into structured conceptual understanding. This proces

MIRAGE: A Micro-Interaction Relational Architecture for Grounded Exploration in Multi-Figure Artworks

arXiv:2604.23788v1 Announce Type: new Abstract: Appreciating multi-figure paintings requires understanding how characters relate through subtle cues like gaze alignment, gesture, and spatial arrangeme

safetyarxiv-cs-cv

Nvidia introduces Nemotron 3 Nano Omni with vision and speech for powerful agentic AI use

model-releasessiliconangle

Nvidia Corp. today launched a powerful reasoning artificial intelligence model that unifies text, vision and speech, capable of acting as the “brains” of faster, smarter agentic AI applications. Dubbe

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning

arXiv:2604.23036v1 Announce Type: cross Abstract: Despite MoE models leading many benchmarks, supervised fine-tuning (SFT) for the MoE architectures remains difficult because its router layers are fra

safetyarxiv-cs-cl

Revisiting Greedy Decoding for Visual Question Answering: A Calibration Perspective

arXiv:2604.23443v1 Announce Type: new Abstract: Stochastic sampling strategies are widely adopted in large language models (LLMs) to balance output coherence and diversity. These heuristics are often

Tutorials

Robust Grounding with MLLMs against Occlusion and Small Objects via Language-guided Semantic Cues

arXiv:2604.24036v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains undere

tutorialsarxiv-cs-cv

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

arXiv:2604.24544v1 Announce Type: new Abstract: The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific eval

Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations

arXiv:2604.24562v1 Announce Type: new Abstract: Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requir

Local Ai

Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Set

arXiv:2502.03669v3 Announce Type: replace-cross Abstract: AI methods, such as generative models and reinforcement learning, have recently been applied to combinatorial optimization (CO) problems, espe

local-aiarxiv-cs-ai

Verifying Quantized GNNs With Readout Is Decidable But Highly Intractable

arXiv:2510.08045v2 Announce Type: replace-cross Abstract: We introduce a logical language for reasoning about quantized aggregate-combine graph neural networks with global readout (ACR-GNNs). We provi

Visual Funnel: Resolving Contextual Blindness in Multimodal Large Language Models

arXiv:2512.10362v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) demonstrate impressive reasoning capabilities, but often fail to perceive fine-grained visual details

A Probabilistic Framework for Hierarchical Goal Recognition

arXiv:2604.22256v1 Announce Type: cross Abstract: Goal recognition aims to infer an agent's goal from observations of its behaviour. In realistic settings, recognition can benefit from exploiting hier

AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection

arXiv:2602.11931v2 Announce Type: replace-cross Abstract: Evolutionary agentic systems intensify the trade-off between computational efficiency and reasoning capability by repeatedly invoking large la

Aggregate vs. Personalized Judges in Business Idea Evaluation: Evidence from Expert Disagreement

arXiv:2604.22517v1 Announce Type: new Abstract: Evaluating LLM-generated business ideas is often harder to scale than generating them. Unlike standard NLP benchmarks, business idea evaluation relies o

Dissociating Decodability and Causal Use in Bracket-Sequence Transformers

arXiv:2604.22128v1 Announce Type: new Abstract: When trained on tasks requiring an understanding of hierarchical structure, transformers have been found to represent this hierarchy in distinct ways: i

Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting

arXiv:2604.22580v1 Announce Type: cross Abstract: As the demand to integrate Artificial Intelligence into high-stakes environments continues to grow, explaining the reasoning behind neural-network pre

researcharxiv-cs-lg

Local Ai

Feedback Over Form: Why Execution Feedback Matters More Than Pipeline Topology in 1-3B Code Generation

arXiv:2604.21950v1 Announce Type: cross Abstract: Small language models (1-3B) are practical to run locally, but individually limited on harder code generation tasks. We ask whether composing them int

local-aiarxiv-cs-ai

Applications

@idarbek Having your backups on the same vendor as your production database puts you at risk of your vendor banning your account for some re…

applicationssimon-willison--x

@idarbek Having your backups on the same vendor as your production database puts you at risk of your vendor banning your account for some reason (like billing messups, or detected CSAM in user-uploade

QuantClaw: Precision Where It Matters for OpenClaw

arXiv:2604.22577v1 Announce Type: new Abstract: Autonomous agent systems such as OpenClaw introduce significant efficiency challenges due to long-context inputs and multi-turn reasoning. This results

The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

arXiv:2601.12979v3 Announce Type: replace Abstract: The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive

agentsarxiv-cs-cl

The Download: DeepSeek’s latest AI breakthrough, and the race to build world models

model-releasesmit-tech-review

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Three reasons why DeepSeek’s new model matters On Friday, Chin

The people building the most powerful technology in history cannot tell you what is happening inside their own systems. This is insane. We s…

The people building the most powerful technology in history cannot tell you what is happening inside their own systems. This is insane. We started the Torchbearer Community for exactly this reason. Re

safetyconnor-leahy--x

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

arXiv:2505.20435v3 Announce Type: replace-cross Abstract: Existing interpretability methods for Large Language Models (LLMs) predominantly capture linear directions or isolated features. This overlook

Industry

This is why OpenAI was created

This is why OpenAI was created Elon Musk turned down all shares when he left OpenAI because he believed nonprofits are not meant for self-enrichment. 'The reason I founded OpenAI was because I was con

industryelon-musk--x

Describe Seattle:

researchfrancois-chollet--x

Describe Seattle: I want to live near the sea and I want to live near the forest and I want to live near the mountains and I want to live near a café and I want to live near a library and I want to li

26 Apr 2026

Industry

5.5 is so earnest 'little engine that could' energy

Sam Altman praised OpenAI's o1 model (version 5.5) for its earnest, persistent approach to problem-solving, comparing it to the 'little engine that could' mentality. The comment reflects Altman's pers

industrysam-altman--x

25 Apr 2026

4⃣4⃣4⃣4⃣

model-releasestogether-ai--x

4⃣4⃣4⃣4⃣ Introducing DeepSeek V4 Pro, a long-context model with hybrid attention, three reasoning modes, and SOTA coding performance. AI natives can now use DeepSeek V4 Pro on Together AI and benefit

Active Data

arXiv:2604.21044v1 Announce Type: new Abstract: In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specificat

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management

arXiv:2604.21209v1 Announce Type: new Abstract: Online reviews have played a pivotal role in consumers' decision-making processes. Existing research has highlighted the significant impact of manageria

Tutorials

Architecture of an AI-Based Automated Course of Action Generation System for Military Operations

arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex

tutorialsarxiv-cs-ai

ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response

model-releasesarxiv-cs-cv

arXiv:2604.21199v1 Announce Type: cross Abstract: Time series question-answering (TSQA), in which we ask natural language questions to infer and reason about properties of time series, is a promising

AUDITA: A New Dataset to Audit Humans vs. AI Skill at Audio QA

model-releasesarxiv-cs-cl

arXiv:2604.21766v1 Announce Type: new Abstract: Existing audio question answering benchmarks largely emphasize sound event classification or caption-grounded queries, often enabling models to succeed

Building a Precise Video Language with Human-AI Oversight

model-releasesarxiv-cs-ai

arXiv:2604.21718v1 Announce Type: cross Abstract: Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmark

Applications

Capabilities and Evaluation Biases of Large Language Models in Classical Chinese Poetry Generation: A Case Study on Tang Poetry

arXiv:2510.15313v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to creative domains, yet their performance in classical Chinese poetry generation and evaluati

applicationsarxiv-cs-cl

Context Unrolling in Omni Models

arXiv:2604.21921v1 Announce Type: new Abstract: We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representati

researcharxiv-cs-cv

Dementia classification from spontaneous speech using wrapper-based feature selection

arXiv:2502.03484v2 Announce Type: replace-cross Abstract: Dementia encompasses a group of syndromes that impair cognitive functions such as memory, reasoning, and the ability to perform daily activiti

researcharxiv-cs-lg

ERA: Evidence-based Reliability Alignment for Honest Retrieval-Augmented Generation

arXiv:2604.20854v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds language models in factual evidence but introduces critical challenges regarding knowledge conflicts betw

EVENT5Ws: A Large Dataset for Open-Domain Event Extraction from Documents

model-releasesarxiv-cs-cl

arXiv:2604.21890v1 Announce Type: new Abstract: Event extraction identifies the central aspects of events from text. It supports event understanding and analysis, which is crucial for tasks such as in

How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models

arXiv:2604.21106v1 Announce Type: cross Abstract: We measure how much one extra recurrence is worth to a looped (depth-recurrent) language model, in equivalent unique parameters. From an iso-depth swe

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems

model-releasesarxiv-cs-ai

arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl

Multimodal Bayesian Network for Robust Assessment of Casualties in Autonomous Triage

arXiv:2512.18908v2 Announce Type: replace Abstract: Mass Casualty Incidents can overwhelm emergency medical systems and resulting delays or errors in the assessment of casualties can lead to preventab