Search: “reasoning”

RobOralScan: Learning Active Intraoral Scanning for Robotic Dental Reconstruction

arXiv:2606.26955v1 Announce Type: new Abstract: Intraoral scanning is widely used for digital optical impressions in prosthodontic, implant, and orthodontic treatment, but full-arch and long-span scan

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Model Releases

Running the Gauntlet: Re-evaluating the Capabilities of Agents Beyond Familiar Environments

DGX agent

arXiv:2606.14397v2 Announce Type: replace Abstract: As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabi

model-releasesarxiv-cs-lg

26 Jun 2026

Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMs

arXiv:2508.03247v2 Announce Type: replace Abstract: Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals r

safetyarxiv-cs-cl

Local Ai

Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting

arXiv:2606.26487v1 Announce Type: cross Abstract: Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet th

local-aiarxiv-cs-ai

The Capability Frontier: Benchmarks Miss 82% of Model Performance

arXiv:2606.26836v1 Announce Type: new Abstract: Existing benchmarks typically report accuracy for a single model on a single run. This systematically understates real-world LLM capabilities, particula

The Inattentional Gap: Task-Conditioned Language and Vision Models Omit the Safety-Critical Signals They Can Otherwise Report

arXiv:2606.26529v1 Announce Type: cross Abstract: AI safety is evaluated by how reliably a model detects the hazards it is told to find, yet accidents often arise from the hazard no one specified. We

The Spec Growth Engine: Spec-Anchored, Code-Coupled, Drift-Enforced Architecture for AI-Assisted Software Development

arXiv:2606.27045v1 Announce Type: cross Abstract: AI coding agents dramatically accelerate implementation speed but introduce two structural failure modes that existing spec-driven approaches do not f

The Verification Horizon: No Silver Bullet for Coding Agent Rewards

arXiv:2606.26300v1 Announce Type: new Abstract: A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inverted: as foun

safetyarxiv-cs-ai

Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery

arXiv:2606.26204v1 Announce Type: new Abstract: Floods frequently impact regions around the world. Rapid and accurate flood detection is crucial for emergency response and timely mitigation of human a

safetyarxiv-cs-lg

Tuning Language Models by Mixture-of-Depths Ensemble

arXiv:2410.13077v2 Announce Type: replace-cross Abstract: Transformer-based Large Language Models (LLMs) traditionally rely on final-layer loss for finetuning and final-layer representations for predi

UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from ex…

model-releasesclem-delangue--x

UBS says 60% of companies now watching AI budgets are moving to cheaper models and open-source Chinese models The pressure is coming from extreme bills, including users spending up to $35K/month, team

VisNec: Measuring and Leveraging Visual Necessity for Multimodal Instruction Tuning

arXiv:2603.01195v2 Announce Type: replace-cross Abstract: The effectiveness of multimodal instruction tuning depends not only on dataset scale, but critically on whether training samples genuinely req

When Actions Go Off-Task: Detecting and Correcting Misaligned Actions in Computer-Use Agents

model-releasesarxiv-cs-cl

arXiv:2602.08995v2 Announce Type: replace Abstract: Computer-use agents (CUAs) have made tremendous progress in the past year, yet they still frequently produce misaligned actions that deviate from th

A Probabilistic Framework for LLM-Based Model Discovery

arXiv:2602.18266v2 Announce Type: replace Abstract: Automated methods for discovering mechanistic simulator models from observational data offer a promising path toward accelerating scientific progres

agentsarxiv-cs-lg

Anthropic says Alibaba must be punished for largest Claude cloning attack

model-releasesars-technica

Anthropic accused Alibaba of a coordinated, industrial-scale operation to illicitly scrape data from Claude , using nearly 25,000 fraudulent accounts to generate more than 28.8 million exchanges betwe

Are We There Yet? Exploring the Capabilities of MLLMs in Assistive AI Applications

model-releasesarxiv-cs-cv

arXiv:2606.25084v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have redefined visual understanding by combining vision encoders with large-scale language models. This unified

ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments

arXiv:2606.25207v1 Announce Type: cross Abstract: Hyperparameter Optimization (HPO) is essential for maximizing machine learning model performance, and its core challenge is sample efficiency: finding

safetyarxiv-cs-cl

Beyond a Shadow of a Doubt: Close Proximity Geometry Reconstruction Using FMCW Radar Shadow Effects

arXiv:2606.25829v1 Announce Type: new Abstract: Reliable perception in adverse conditions remains challenging for autonomous systems, as cameras and LiDAR degrade in poor lighting or weather. Millimet

agentsarxiv-cs-ro

Causality-Based Parametric Control Barrier Function for Safe Multi-Vehicle Interaction

arXiv:2606.25134v1 Announce Type: new Abstract: Safe control has been widely studied in various safety-critical applications, for instance, autonomous driving. In order to ensure the autonomous vehicl

CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts

arXiv:2602.17663v2 Announce Type: replace-cross Abstract: HIPE-2026 is a CLEF evaluation lab dedicated to person-place relation extraction from noisy, multilingual historical texts. Building on the HI

researcharxiv-cs-cl

Tutorials

Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning

arXiv:2606.25357v1 Announce Type: new Abstract: State abstraction plays a key role in scaling reinforcement learning to complex but structured systems. In studying such systems, a wide range of behavi

tutorialsarxiv-cs-lg

Decoupling Semantics and Geometric Grounding: Spatial Visual Prompts for Language-Conditioned Imitation Learning

arXiv:2606.25360v1 Announce Type: new Abstract: While end-to-end Vision-Language-Action (VLA) models show promise in robotic manipulation, their monolithic paradigm inherently couples semantic reasoni

Local Ai

EmotionAI: A Privacy-Preserving Computational Intelligence Pipeline for Speech-Emotion-Grounded Conversational Analysis

arXiv:2606.24941v1 Announce Type: cross Abstract: Reviewing recorded interviews for affective cues such as composure, hesitation and agitation is slow and subjective, and cloud services that could aut

local-aiarxiv-cs-ai

Expresso-AI: Explainable Video-Based Deep Learning Models for Depression Diagnosis

arXiv:2606.25606v1 Announce Type: new Abstract: Given the widespread prevalence of depression and its consequential impact on individuals and society, it is crucial to obtain objective measures for ea

researcharxiv-cs-cv

Failure Modes of Large Language Models on Research-Level Mathematics: A Taxonomy and an Empirical Characterisation

arXiv:2606.24902v1 Announce Type: cross Abstract: The 'First Proof' benchmark [1] posed ten research-level mathematics questions to the strongest publicly available LLMs and found them consistently wr

GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization

arXiv:2505.13731v4 Announce Type: replace Abstract: Worldwide image geolocalization-the task of predicting GPS coordinates from images taken anywhere on Earth-poses a fundamental challenge due to the

researcharxiv-cs-cv

Local Ai

Graph-Based Phonetic Error Correction of Noisy ASR

arXiv:2606.24889v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems, despite low overall word error rates, produce residual lexical errors that disproportionately affect semanti

local-aiarxiv-cs-cl

GroundSet: A Cadastral-Grounded Dataset for Spatial Understanding with Vector Data

model-releasesarxiv-cs-cv

arXiv:2603.14609v2 Announce Type: replace Abstract: Precise spatial understanding in Earth Observation is essential for translating raw aerial imagery into actionable insights for critical application

Tutorials

Interpretable Concept-Guided Polynomial Tabular Kolmogorov-Arnold Network for EEG-Based Mild Cognitive Impairment Detection

arXiv:2606.25434v1 Announce Type: new Abstract: Early and scalable detection of mild cognitive impairment (MCI) remains an unresolved clinical challenge. Existing EEG-based screening approaches are co

tutorialsarxiv-cs-lg

Just had a great discussion on dynamic workflows. Rough notes: - applies to a very small set of use cases - think of it as a new paradigm of…

Just had a great discussion on dynamic workflows. Rough notes: - applies to a very small set of use cases - think of it as a new paradigm of (test-time compute) TTC - strong for hill-climbing research

agentsdair-ai--x

Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models

arXiv:2504.09910v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sen

researcharxiv-cs-cl

LibEvoBench: Probing Temporal Knowledge Stratification in Code Generation Models

arXiv:2606.25402v1 Announce Type: cross Abstract: Large software projects often depend on older versions of libraries, even as APIs continue to evolve across releases. This creates a challenge for LLM

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction

arXiv:2606.25651v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare settings, accurate error detection and correction in generated or existing text

safetyarxiv-cs-cl

Tools

More on how we're constraining eval environments so that scores better reflect model intelligence: http://cursor.com/blog/reward-hacking-cod…

Cursor discusses methods for improving AI evaluation environments to prevent reward hacking and ensure benchmark scores more accurately measure model capabilities rather than exploitation of evaluatio

toolscursor--x

Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts

arXiv:2606.25935v1 Announce Type: new Abstract: Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of

researcharxiv-cs-cl

Applications

PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking

arXiv:2603.19305v2 Announce Type: replace-cross Abstract: Humanoid robots are expected to execute agile and expressive whole-body motions in real-world settings. Existing text-to-motion generation mod

applicationsarxiv-cs-cv

Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows

arXiv:2604.25345v2 Announce Type: replace Abstract: Agentic AI systems are increasingly being integrated into scientific workflows, yet their behavior under realistic conditions remains insufficiently

agentsarxiv-cs-ai

Reflective VLA: In-Context Action Consequences Make VLAs Generalize

arXiv:2606.25215v1 Announce Type: new Abstract: Most vision-language-action (VLA) models are reactive: they predict the next action from the current instruction and observation, implicitly assuming th

safetyarxiv-cs-cv

RoDyn: Taming Interactive Robot-Dynamic 2.5D World Model for Robotic Manipulation

arXiv:2510.09036v2 Announce Type: replace Abstract: Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently l

agentsarxiv-cs-ro

Same Evidence, Different Answer: Auditing Order Sensitivity in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.26079v1 Announce Type: new Abstract: Standard benchmarks for multimodal large language models (MLLMs) score each item on one canonical ordering and miss whether order-irrelevant shuffling c

TheoremGraph: Bridging Formal and Informal Mathematics

arXiv:2606.25363v1 Announce Type: cross Abstract: Mathematical knowledge is organized around statements and their dependencies, but this structure is exposed unevenly: informal papers cite mostly at t

agentsarxiv-cs-ai

TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control

arXiv:2601.14945v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) models offer semantic generalization but suffer from high inference latency, limiting them to low-frequency

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG

arXiv:2606.25191v1 Announce Type: cross Abstract: Multi-agent document assessment for retrieval-augmented generation is computationally expensive, driving practitioners toward smaller, deployable mode

agentsarxiv-cs-cl

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

researcharxiv-cs-ai

update with some context and additional thoughts: https://open.substack.com/pub/garymarcus/p/the-generative-ai-fizzle?utm_source=app-post-st…

Gary Marcus discusses concerns about generative AI's limitations and potential overhyping of the technology, arguing that initial enthusiasm may not translate into sustained practical breakthroughs as

safetygary-marcus--x

VPA-Guard: Defending and Benchmarking Image-to-Video Generation Against Visual Prompt Attacks

model-releasesarxiv-cs-cv

arXiv:2606.25592v1 Announce Type: new Abstract: Recent advancements in Image-to-Video (I2V) generation have transformed input images from simple appearance references into interactive control interfac

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

arXiv:2606.25041v1 Announce Type: new Abstract: We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex

researcharxiv-cs-cv

What Does It Mean to Break a Distillation Defense?

arXiv:2606.25059v1 Announce Type: cross Abstract: Black-box LLMs (accessible only via API) are vulnerable to distillation attacks, in which an attacker queries the model and trains a student on its ou

safetyarxiv-cs-ai