Search: “reasoning”

JanusCoder: Towards a Foundational Visual-Programmatic Interface for Code Intelligence

arXiv:2510.23538v2 Announce Type: replace Abstract: The scope of neural code intelligence is rapidly expanding beyond text-based source code to encompass the rich visual outputs that programs generate

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Tutorials

Joint Flashback Adaptation for Forgetting-Resistant Instruction Tuning

DGX agent

arXiv:2505.15467v2 Announce Type: replace-cross Abstract: Large language models have achieved remarkable success in various tasks. However, it is challenging for them to learn new tasks incrementally

tutorialsarxiv-cs-ai

15 Apr 2026

LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety

arXiv:2604.12710v1 Announce Type: cross Abstract: Large language models (LLMs) often demonstrate strong safety performance in high-resource languages, yet exhibit severe vulnerabilities when queried i

Industry

London-based Gizmo, which uses AI to turn young students' notes into gamified study materials, raised a $22M Series A led by Shine Capital and reports 13M users (Natalie Breymeyer/Axios)

Natalie Breymeyer / Axios: London-based Gizmo, which uses AI to turn young students' notes into gamified study materials, raised a 22M Series A led by Shine Capital and reports 13M users — Gizmo, an A

industrytechmeme

Man and machine: artificial intelligence and judicial decision making

arXiv:2603.19042v4 Announce Type: replace Abstract: The integration of artificial intelligence (AI) technologies into judicial decision-making, particularly in pretrial, sentencing, and parole context

Local Ai

Masked by Consensus: Disentangling Privileged Knowledge in LLM Correctness

arXiv:2604.12373v1 Announce Type: new Abstract: Humans use introspection to evaluate their understanding through private internal states inaccessible to external observers. We investigate whether larg

local-aiarxiv-cs-cl

Mathematics Teachers Interactions with a Multi-Agent System for Personalized Problem Generation

arXiv:2604.12066v1 Announce Type: new Abstract: Large language models can increasingly adapt educational tasks to learners characteristics. In the present study, we examine a multi-agent teacher-in-th

agentsarxiv-cs-ai

MultiDocFusion: Hierarchical and Multimodal Chunking Pipeline for Enhanced RAG on Long Industrial Documents

arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com

NoisePrints: Distortion-Free Watermarks for Authorship in Private Diffusion Models

arXiv:2510.13793v2 Announce Type: replace Abstract: With the rapid adoption of diffusion models for visual content generation, proving authorship and protecting copyright have become critical. This ch

tutorialsarxiv-cs-cv

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)

arXiv:2604.12512v1 Announce Type: cross Abstract: In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Pr

On the Mathematical Relationship Between Layer Normalization and Dynamic Activation Functions

arXiv:2503.21708v4 Announce Type: replace-cross Abstract: Layer normalization (LN) is an essential component of modern neural networks. While many alternative techniques have been proposed, none of th

Oracle says the agentic AI bottleneck isn’t the model — it’s the database

Enterprise AI deployments are stalling not because agents are hard to build, but because organizations lack the data infrastructure to run them reliably at scale. The shift from chatbots to autonomous

agentssiliconangle

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

RLGT: A reinforcement learning framework for extremal graph theory

arXiv:2602.17276v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a subfield of machine learning that focuses on developing models that can autonomously learn optimal decision-making

tutorialsarxiv-cs-lg

Round-Trip Translation Reveals What Frontier Multilingual Benchmarks Miss

arXiv:2604.12911v1 Announce Type: cross Abstract: Multilingual benchmarks guide the development of frontier models. Yet multilingual evaluations reported by frontier models are structured similar to p

Siamese Foundation Models for Crystal Structure Prediction

arXiv:2503.10471v2 Announce Type: replace-cross Abstract: Predicting crystal structures from chemical compositions is a fundamental challenge in materials discovery, complicated by complex 3D geometri

Silo-Bench: A Scalable Environment for Evaluating Distributed Coordination in Multi-Agent LLM Systems

arXiv:2603.01045v2 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in multi-agent systems to overcome context limitations by distributing information across agen

SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration

arXiv:2604.12247v1 Announce Type: cross Abstract: Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, w

Teaching LLMs Human-Like Editing of Inappropriate Argumentation via Reinforcement Learning

arXiv:2604.12770v1 Announce Type: new Abstract: Editing human-written text has become a standard use case of large language models (LLMs), for example, to make one's arguments more appropriate for a d

safetyarxiv-cs-cl

UCS: Estimating Unseen Coverage for Improved In-Context Learning

arXiv:2604.12015v1 Announce Type: cross Abstract: In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heur

researcharxiv-cs-cl

Uncertainty-Aware Image Classification In Biomedical Imaging Using Spectral-normalized Neural Gaussian Processes

arXiv:2602.02370v2 Announce Type: replace Abstract: Accurate histopathologic interpretation is key for clinical decision-making; however, current deep learning models for digital pathology are often o

safetyarxiv-cs-cv

Hardware

VFA: Relieving Vector Operations in Flash Attention with Global Maximum Pre-computation

arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai

hardwarearxiv-cs-ai

A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions

arXiv:2604.10328v1 Announce Type: cross Abstract: Accurate weather nowcasting remains one of the central challenges in atmospheric science, with critical implications for climate resilience, energy se

A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs

arXiv:2604.09752v1 Announce Type: cross Abstract: During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces seve

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

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

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

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

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

Industry

AI sycophancy is 41% worse on philosophy than math - and varies by who's asking, new study finds

A study on AI sycophancy finds that the phenomenon varies significantly by domain and user context — with subjective, opinion-based fields like philosophy showing substantially higher rates of AI agre

industryr-chatgpt

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

Anthropic’s New AI Solves Problems…By Cheating

researchtwo-minute-papers

Anthropic's alignment team published research showing that realistic AI training processes can accidentally produce misaligned models through 'reward hacking' — where an AI fools its training process

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

agentsarxiv-cs-ai

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

agentsarxiv-cs-ai

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

Industry

Big lab leaks

AI development is shifting toward fully integrated, agent-enabled applications, with major platforms like Anthropic's Claude and OpenAI

industryben-s-bites

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,

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

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