Search: “reasoning”

CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language

model-releasesarxiv-cs-ai

arXiv:2604.22367v1 Announce Type: cross Abstract: Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs t

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CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models

DGX agent

arXiv:2604.22238v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume

applicationsarxiv-cs-ro

27 Apr 2026

Conditional anomaly detection using soft harmonic functions: An application to clinical alerting

arXiv:2604.21956v1 Announce Type: new Abstract: Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detect

applicationsarxiv-cs-lg

Conditional Diffusion Posterior Alignment for Sparse-View CT Reconstruction

arXiv:2604.21960v1 Announce Type: cross Abstract: Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, t

safetyarxiv-cs-cv

Cost-Effective Communication: An Auction-based Method for Language Agent Interaction

arXiv:2511.13193v2 Announce Type: replace Abstract: Multi-agent systems (MAS) built on large language models (LLMs) often suffer from inefficient 'free-for-all' communication, leading to exponential t

agentsarxiv-cs-ai

Local Ai

Creative studios are being asked to do something fundamentally different now. Not just great work, but foundational systems for experience, …

Creative studios are being asked to do something fundamentally different now. Not just great work, but foundational systems for experience, brand, and content that their clients can own, extend, and b

local-aicomfyui--x

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale

arXiv:2604.00813v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models,

agentsarxiv-cs-ai

Estimating Tail Risks in Language Model Output Distributions

arXiv:2604.22167v1 Announce Type: cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-level scale. As a result, the safety of these models is increa

safetyarxiv-cs-ai

EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges

model-releasesarxiv-cs-cv

arXiv:2604.22595v1 Announce Type: new Abstract: CLIP has demonstrated strong generalization in visual domains through natural language supervision, even for video action recognition. However, most exi

Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Ever…

applicationsethan-mollick--x

Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Everything else (job impact, potential risks, etc.) is downstrea

Fast, close, non-singular and property-preserving approximations of entropic measures

arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key

Local Ai

From Local to Cluster: A Unified Framework for Causal Discovery with Latent Variables

arXiv:2604.22416v1 Announce Type: cross Abstract: Latent variables pose a fundamental challenge to causal discovery and inference. Conventional local methods focus on direct neighbors but fail to prov

local-aiarxiv-cs-ai

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

Tutorials

GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms

arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th

tutorialsarxiv-cs-cv

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair

arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen

How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks

model-releasesarxiv-cs-cl

arXiv:2604.22750v1 Announce Type: new Abstract: The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that requi

How do AI Agents spend your money? Most teams treat agent token costs as a rounding error even though the data says they shouldn't. New pape…

How do AI Agents spend your money? Most teams treat agent token costs as a rounding error even though the data says they shouldn't. New paper presents the first systematic study of how agents actually

agentsdair-ai--x

Initial results of the Digital Consciousness Model

arXiv:2601.17060v2 Announce Type: replace-cross Abstract: Artificially intelligent systems have become remarkably sophisticated. They hold conversations, write essays, and seem to understand context i

Inter-Stance: A Dyadic Multimodal Corpus for Conversational Stance Analysis

arXiv:2604.22739v1 Announce Type: new Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as

researcharxiv-cs-cv

Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model

arXiv:2512.16251v5 Announce Type: replace-cross Abstract: We introduce the Consensus-Bottleneck Asset Pricing Model (CB-APM), which embeds aggregate analyst consensus as a structural bottleneck, treat

Introducing Background Temperature to Characterise Hidden Randomness in Large Language Models

arXiv:2604.22411v1 Announce Type: new Abstract: Even when decoding with temperature T=0, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machin

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation

model-releasesarxiv-cs-cv

arXiv:2604.22302v1 Announce Type: new Abstract: Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reliab

Lifting Unlabeled Internet-level Data for 3D Scene Understanding

arXiv:2604.01907v2 Announce Type: replace-cross Abstract: Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this pap

Mapping a smarter future with BigQuery and Google Earth AI models and datasets

model-releasesgoogle-cloud-ai

Last year we introduced new geospatial analytics capabilities integrated for BigQuery. Building on this, we announced an expanded suite of tools at Google Cloud Next ‘26, designed to help your busines

Mechanistic Interpretability of Antibody Language Models Using SAEs

arXiv:2512.05794v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) are a mechanistic interpretability technique that have been used to provide insight into learned concepts within la

Multi-Token Prediction via Self-Distillation

arXiv:2602.06019v2 Announce Type: replace Abstract: Existing techniques for accelerating language model inference, such as speculative decoding, require training auxiliary speculator models and buildi

MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compression

arXiv:2410.21548v3 Announce Type: replace Abstract: Large language models have drastically changed the prospects of AI by introducing technologies for more complex natural language processing. However

On Star Price's new @hitpausepod podcast, ControlAI's US Director Connor Leahy (@NPCollapse) explains how AIs can already tell when they're …

On Star Price's new @hitpausepod podcast, ControlAI's US Director Connor Leahy (@NPCollapse) explains how AIs can already tell when they're being tested. Currently, we can still catch them cheating, b

safetyconnor-leahy--x

Industry

Partnering with Ineffable Intelligence: A Superlearner for the Era of Experience

Ineffable Intelligence is building a superlearner—an AI system that discovers knowledge through its own experience rather than human data, using reinforcement learning without pre-training. The compan

industrysequoia-capital

Privacy Leakage via Output Label Space and Differentially Private Continual Learning

arXiv:2411.04680v5 Announce Type: replace Abstract: Differential privacy (DP) is a formal privacy framework that enables training machine learning (ML) models while protecting individuals' data. As po

researcharxiv-cs-lg

Processing loan applications traditionally takes a staggering amount of time going through paperwork - ~dozens of hours every month looking …

model-releasesjerry-liu--x

Processing loan applications traditionally takes a staggering amount of time going through paperwork - ~dozens of hours every month looking at the loan application and cross-checking it with user-subm

ReCast: Recasting Learning Signals for Reinforcement Learning in Generative Recommendation

arXiv:2604.22169v1 Announce Type: cross Abstract: Generic group-based RL assumes that sampled rollout groups are already usable learning signals. We show that this assumption breaks down in sparse-hit

safetyarxiv-cs-ai

Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems

arXiv:2604.22154v1 Announce Type: cross Abstract: Emerging AI systems in behavioral health and psychiatry use multi-step or multi-agent LLM pipelines for tasks like assessing self-harm risk and screen

safetyarxiv-cs-ai

Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities

arXiv:2604.22749v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, in

applicationsarxiv-cs-cl

Rethinking Token Pruning for Historical Screenshots in GUI Visual Agents: Semantic, Spatial, and Temporal Perspectives

arXiv:2603.26041v3 Announce Type: replace Abstract: In recent years, GUI visual agents built upon Multimodal Large Language Models (MLLMs) have demonstrated strong potential in navigation tasks. Howev

researcharxiv-cs-cv

Spontaneous Persuasion: An Audit of Model Persuasiveness in Everyday Conversations

arXiv:2604.22109v1 Announce Type: cross Abstract: Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs t

Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models

arXiv:2510.11586v2 Announce Type: replace Abstract: Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LL

safetyarxiv-cs-cl

This is totally wrong. Blaming the user is missing the point that (a) coding agents have been overhyped and (b) can’t reliably obey the rule…

This is totally wrong. Blaming the user is missing the point that (a) coding agents have been overhyped and (b) can’t reliably obey the rules given to them in system prompts and other guardrails. Sorr

safetygary-marcus--x

Tracing the complexity profiles of different linguistic phenomena through the intrinsic dimension of LLM representations

arXiv:2601.03779v2 Announce Type: replace Abstract: We explore intrinsic dimension (ID) of LLM representations as a marker of linguistic complexity. Specifically, we test whether ID differences across

Uni-Encoder Meets Multi-Encoders: Representation Before Fusion for Brain Tumor Segmentation with Missing Modalities

arXiv:2604.22177v1 Announce Type: new Abstract: Multimodal MRI offers complementary information for brain tumor segmentation, but clinical scans often lack one or more modalities, which degrades segme

researcharxiv-cs-cv

UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents

model-releasesarxiv-cs-cl

arXiv:2602.07038v2 Announce Type: replace-cross Abstract: Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual qual

Using Embedding Models to Improve Probabilistic Race Prediction

arXiv:2604.22555v1 Announce Type: new Abstract: Estimating racial disparity requires individual-level race data, which are often unavailable due to the sensitivity of collecting such information. To a

When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Books

arXiv:2604.21993v1 Announce Type: new Abstract: We study the detection of transient liquidity erosion ('crumbling quotes') in electronic limit order books, where observable quote deterioration may ref

agentsarxiv-cs-lg

NEW paper from Alibaba. A 30B MoE with only 3B active params matches Qwen3-235B on real tool-use workloads. AgenticQwen-30B-A3B: 50.2 averag…

NEW paper from Alibaba. A 30B MoE with only 3B active params matches Qwen3-235B on real tool-use workloads. AgenticQwen-30B-A3B: 50.2 average on TAU-2 + BFCL-V4 Multi-Turn. AgenticQwen-8B: 47.4. Both

model-releasesdair-ai--x

26 Apr 2026

Whether there or more or less jobs, they will certainly change, and professions will compete to gain jurisdiction over valuable ones, in lar…

applicationsethan-mollick--x

Whether there or more or less jobs, they will certainly change, and professions will compete to gain jurisdiction over valuable ones, in large part through regulation, requiring credentials, and appea

26 Apr 2026

Balanced Performance Across Artistic Styles： More uniform quality across diverse aesthetic domains, effectively reducing style-dependent qua…

Qwen's latest model improvements focus on achieving more consistent and uniform performance quality across different artistic styles and aesthetic domains, reducing the variability in output quality t

model-releasesqwen--x

25 Apr 2026

Comprehensive Multilingual Text Rendering： Better glyph accuracy, more consistent typography, and cleaner layouts even in complex compositio…

Comprehensive Multilingual Text Rendering： Better glyph accuracy, more consistent typography, and cleaner layouts even in complex compositions. It handles mixed-language scenarios more gracefully as w

model-releasesqwen--x

25 Apr 2026

Every time I tell AI utopianists that biology is too complex for AI to 'solve', they cite the success of AlphaFold. No, AlphaFold did not 's…