All entries

Can LLMs Introspect? A Reality Check

arXiv:2605.26242v1 Announce Type: new Abstract: Can large language models detect and report their own internal states? A number of studies have argued that the answer to this question is yes. We argue

Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models

arXiv:2605.27243v1 Announce Type: new Abstract: Large vision-language models increasingly rely on long-context modeling to reason over documents, hour-level videos, and long-horizon agent trajectories

agentsarxiv-cs-cv

27 May 2026

Tutorials

Can VLA Models Learn from Real-World Data Continually without Forgetting?

arXiv:2605.26820v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide a promising foundation for general-purpose robotics. However, their successful deployment in real-world scen

tutorialsarxiv-cs-ro

Local Ai

CART Random Forests as Sequential Allocation over Random Opportunity Sets: A Stochastic-Control Theory of Ensemble Risk

arXiv:2605.26675v1 Announce Type: cross Abstract: CART random forests are among the most widely used modern predictive methods, with well-documented empirical success. Yet, at the mechanistic level, t

local-aiarxiv-cs-lg

Cast a Wider Net: Coordinated Pass@K Policy Optimization for Code Reasoning

arXiv:2605.27000v1 Announce Type: cross Abstract: Repeated sampling with a verifier is the standard way to allocate test-time compute for code generation, with pass@K as the canonical metric. Yet the

Causal Representation Learning for Generalisable Recommendation

model-releasesarxiv-cs-lg

arXiv:2605.27043v1 Announce Type: cross Abstract: Predictive models trained on observational data often fail to generalise to the distributions they encounter when deployed, especially when the traini

Tutorials

Causal Risk Minimization for High-Dimensional Treatments

arXiv:2605.27281v1 Announce Type: new Abstract: Predicting the effect of interventions with many possible variations, e.g., therapeutic content that affects mental health outcomes or an earnings call

tutorialsarxiv-cs-lg

Certified Causal Attribution for Real-Time Attack Forensics in 6G Network Slicing

arXiv:2605.26679v1 Announce Type: cross Abstract: Cross-slice attack attribution in 6G networks requires identifying causal propagation chains through shared infrastructure in under 100 ms. Existing m

applicationsarxiv-cs-ai

Cesarean Scar Defect Segmentation in Transvaginal Ultrasound Images: a Dataset and Benchmark

arXiv:2605.26774v1 Announce Type: new Abstract: Cesarean Scar Defect (CSD) is one of the most prevalent complications following cesarean delivery. Transvaginal ultrasonography is widely used for prima

CFG-OEC: Classifier Free Guidance with Orthogonal Error Correction

arXiv:2511.14075v2 Announce Type: replace-cross Abstract: Classifier free guidance is a standard method for conditional sampling in diffusion models, but its sampling rule is not aligned with the obje

Chain Of Thought Compression: A Theoretical Analysis

arXiv:2601.21576v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) has unlocked advanced reasoning abilities of Large Language Models (LLMs) with intermediate steps, yet incurs prohibitive com

ChainCaps: Composition-Safe Tool-Using Agents via Monotonic Capability Attenuation

arXiv:2605.26542v1 Announce Type: cross Abstract: Tool-using agents increasingly operate in open-ended deployment environments, where they compose file systems, web APIs, code interpreters, and enterp

Tutorials

Chaos-SSL: An Attention-Based Self-Supervised Learning Framework with Chaotic Transformation for Medical Image Classification

arXiv:2605.27146v1 Announce Type: new Abstract: Self-Supervised Learning (SSL) has emerged as a powerful paradigm to mitigate the reliance on large, annotated datasets, a common bottleneck in medical

tutorialsarxiv-cs-cv

ChartAct: A Benchmark for Dynamic Chart Understanding

arXiv:2605.26994v1 Announce Type: new Abstract: Charts are widely used to present complex data for analysis and decision making. Existing chart understanding benchmarks mainly focus on static charts,

Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models

arXiv:2605.27311v1 Announce Type: new Abstract: Chart question-answering (QA) benchmarks aim to pose questions that require visual reasoning to correctly answer, but models can often reach solutions t

researcharxiv-cs-cl

CIRCLED: A Multi-turn CIR Dataset with Consistent Dialogues across Domains

arXiv:2605.26734v1 Announce Type: new Abstract: Existing Multi-Turn Composed Image Retrieval (MTCIR) datasets lack dialogue-history consistency and are restricted to the fashion domain. To address the

Cisco and OpenAI redefine enterprise engineering with Codex

Cisco and OpenAI partnered to integrate OpenAI's Codex AI model into Cisco's enterprise engineering tools to enhance software development and automation capabilities. The collaboration aims to improve

applicationsopenai

Industry

Cisco report finds no closed frontier AI model is safe from multi-turn attacks

A new report out today from Cisco Systems Inc. argues that none of the closed flagship large language models it tested can be considered safe once an attacker is allowed to push past a single prompt,

industrysiliconangle

CktGen: Automated Analog Circuit Design with Generative Artificial Intelligence

model-releasesarxiv-cs-lg

arXiv:2410.00995v3 Announce Type: replace Abstract: The automatic synthesis of analog circuits presents significant challenges. Most existing approaches formulate the problem as a single-objective opt

Classification and detection of multiple UAVs using rational Gaussian wavelet neural networks

arXiv:2605.26310v1 Announce Type: new Abstract: The detection of unmanned aerial vehicles (UAVs) is important for the protection of civilian and military infrastructure. In this paper we propose a cos

researcharxiv-cs-lg

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning

model-releasesarxiv-cs-lg

arXiv:2502.03946v5 Announce Type: replace Abstract: Data preprocessing is often paid little attention in machine learning, despite its potentially significant impact on model performance. While automa

Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis

arXiv:2605.26483v1 Announce Type: new Abstract: Medical video diagnosis involves inferring clinical decisions from dynamic tissue responses throughout examination processes. Existing methods rely on a

Closing the Loop in Teleoperation: Episode-Level Data Quality Assessment and Feedback for High-Quality Demonstration Collection

arXiv:2605.26349v1 Announce Type: new Abstract: Industrial automation is at a pivotal moment, as Physical AI is driving a transition from rigid, hand-engineered automation systems toward more flexible

applicationsarxiv-cs-ro

Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal

arXiv:2601.09886v2 Announce Type: replace Abstract: How predictable a word is can be quantified in two ways: using human responses to the cloze task or using probabilities from language models (LMs).W

researcharxiv-cs-cl

CmIVTP: Cross-modal Interaction-based Vessel Trajectory Prediction for Maritime Intelligence

arXiv:2605.26524v1 Announce Type: cross Abstract: Maritime intelligent transportation systems (MITS) are essential for ensuring navigation safety and efficiency in busy waterways. However, accurate ve

CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection

arXiv:2605.26294v1 Announce Type: new Abstract: Skin cancer is a common and fast rising malignancy worldwide. Early detection is critical for improving outcomes. Deep learning models trained on dermos

Co-folding model guided by structural proteomics

arXiv:2605.26192v1 Announce Type: cross Abstract: Protein structure generative models excel at predicting single protein static structures from sequence, but routinely fail to capture the correct conf

Tools

Co-founder and Head of Design at Replit, @HayaOdeh shapes the brand, user experience, and product design of one of the world’s most accessib…

Co-founder and Head of Design at Replit, @HayaOdeh shapes the brand, user experience, and product design of one of the world’s most accessible vibe coding platforms. See her take the stage on day two

toolsreplit--x

CodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning

arXiv:2605.26967v1 Announce Type: new Abstract: Existing video captioning methods struggle to balance visual fidelity and redundancy: holistic captions are compact but lose fine-grained evidence, wher

Cogent Security launches autonomous vulnerability response tools as AI-assisted exploits outpace scanners

model-releasessiliconangle

Cogent Security Inc., a startup that employs agentic artificial intelligence for vulnerability management, today launched two new platform capabilities aimed at compressing enterprise vulnerability re

cognition is now the largest independent agent lab in the world. take the 200% utilization that everyone is hitting from this chart and run …

cognition is now the largest independent agent lab in the world. take the 200% utilization that everyone is hitting from this chart and run out the sales growth from this, i encourage you to go thru t

agentsswyx--x

Local Ai

Collaborative Navigation and Exploration with eta-Sparse Gaussian Processes

arXiv:2605.26304v1 Announce Type: new Abstract: Collaborative navigation of heterogeneous robots in unknown environments poses significant challenges due to sensing, communication, and computational l

local-aiarxiv-cs-ro

Communication Gain and Delay Cost Under Cross-Timestep Delays in Cooperative Multi-Agent Reinforcement Learning

arXiv:2604.03785v2 Announce Type: replace Abstract: Communication is essential for coordination in cooperative multi-agent reinforcement learning under partial observability, yet cross-timestep delays

agentsarxiv-cs-ai

Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes

arXiv:2605.26475v1 Announce Type: cross Abstract: Vision-based metric distance and area measurement remains challenging in large-scale outdoor environments due to long-range sensing, camera zoom, and

applicationsarxiv-cs-ai

CompassDPO: Dynamics-Controlled Direct Preference Optimization for Robust Safety Alignment

arXiv:2603.07211v2 Announce Type: replace Abstract: Direct Preference Optimization (DPO) has become a standard framework for safety alignment, but its reliance on pairwise preference updates makes tra

safetyarxiv-cs-lg

Completely agree, @hwchase17 ! This is the meta-level breakthrough we've all been waiting for. Self-optimizing loops finally feel production…

Completely agree, @hwchase17 ! This is the meta-level breakthrough we've all been waiting for. Self-optimizing loops finally feel production-ready because LangSmith Engine turns evaluation from a manu

safetyharrison-chase--x

completing the loop is paramount most unrecognized step in the development lifecycle is iteration on the process itself

completing the loop is paramount most unrecognized step in the development lifecycle is iteration on the process itself everyone is talking about self-optimizing loops in software & agents. but what d

agentsharrison-chase--x

Completion vs Optimality: Policy Gradient in Long-Horizon Cumulative-Damage Problems

arXiv:2605.26657v1 Announce Type: new Abstract: Long-horizon decision problems with cumulative damage couple locally attractive actions to globally adverse outcomes. We identify two orthogonal failure

Composition Collapse: Stable Factual Knowledge Does Not Imply Compositional Reasoning

arXiv:2605.26789v1 Announce Type: new Abstract: Post-training is routinely evaluated through aggregate benchmark scores that treat multi-hop reasoning as a single capability -- as if a model that answ

Computer use in Fleet is now in public beta! You can now give your agents in Fleet access to secure virtual machines allowing them to own en…

Computer use in Fleet is now in public beta! You can now give your agents in Fleet access to secure virtual machines allowing them to own engineering tasks for you. Use these via Fleet agents in the U

agentsharrison-chase--x

Conceptual Schema Inference for Tabular Datasets using Large Language Models

arXiv:2509.04632v2 Announce Type: replace-cross Abstract: Large collections of tabular data from data lakes, web tables and open data portals often originate from heterogeneous sources, leading to rep

applicationsarxiv-cs-ai

Conceptual Steganography

arXiv:2605.26537v1 Announce Type: new Abstract: Language Models (LMs) emit Chains-of-Thought (CoTs) that drive much of their capability. However, the same sequence that carries useful reasoning can al

researcharxiv-cs-cl

Confounder Detection via Treatment Intent: A New Observational Study Design

arXiv:2605.26413v1 Announce Type: cross Abstract: Understanding the effects of interventions is central to scientific progress, with randomized controlled trials (RCTs) regarded as the gold standard f

Constrained Bayesian Experimental Design via Online Planning

arXiv:2605.26990v1 Announce Type: cross Abstract: Bayesian experimental design (BED) is a principled framework for data-efficient design of sequential experiments. However, existing BED methods are un

safetyarxiv-cs-lg

Constrained Meta Reinforcement Learning with Provable Test-Time Safety

arXiv:2601.21845v2 Announce Type: replace Abstract: Meta reinforcement learning (RL) allows agents to leverage experience across a distribution of tasks on which the agent can train at will, enabling

safetyarxiv-cs-lg

Constraint acquisition needs better benchmarks

arXiv:2605.26279v1 Announce Type: new Abstract: Constraint Acquisition (CA) and related research on the validation and enhancement of Mathematical Programming (MP) models from domain knowledge artifac

Constructing Industrial-Scale Optimization Modeling Benchmark

arXiv:2602.10450v2 Announce Type: replace-cross Abstract: Optimization modeling underpins decision-making in logistics, manufacturing, energy, and finance, yet translating natural-language requirement

ContextGuard: Structured Self-Auditing for Context Learning in Language Models

arXiv:2605.26827v1 Announce Type: cross Abstract: Recent benchmarks reveal that despite strong reasoning capabilities, large language models (LLMs) still struggle to faithfully apply complex contextua