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Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens

arXiv:2505.13775v4 Announce Type: replace-cross Abstract: Recent impressive results from large reasoning models have been interpreted as a triumph of Chain of Thought (CoT), and especially of the proc

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Safety

Beyond the Data Mesh Illusion: Designing Modern AI-augmented Lakehouses to Bridge the Gap Between Theory and Practice

DGX agent

arXiv:2605.27131v1 Announce Type: cross Abstract: Enterprise data platforms face an enduring tension between domain self-service and holistic governance. The data mesh paradigm proposed decentralized

safetyarxiv-cs-ai

27 May 2026

Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning

arXiv:2605.26684v1 Announce Type: cross Abstract: Group-based reinforcement learning (RL) methods have achieved remarkable success in improving the performance of large language models (LLMs) and have

Beyond Transfer Accuracy: Faithful Circuits for Controlled Low-Resource Adaptation

arXiv:2601.08146v3 Announce Type: replace-cross Abstract: Existing circuit discovery methods rely on templated tasks with clean counterfactuals, limiting their use on diverse natural text. We adapt Co

BeyondSWE: Can Current Code Agent Survive Beyond Single-Repo Bug Fixing?

model-releasesarxiv-cs-cl

arXiv:2603.03194v2 Announce Type: replace Abstract: Current code-agent benchmarks primarily evaluate localized issue resolution within a single target repository, leaving under-tested many software en

BhashaSetu: A Data-Centric Approach to Low-Resource Machine Translation

model-releasesarxiv-cs-cl

arXiv:2605.27050v1 Announce Type: new Abstract: We present BhashaSetu, a linguistically enriched English--Marathi parallel dataset addressing persistent data limitations in low-resource neural machine

Bilevel Optimization over Saddle Points of Zero-Sum Markov Games

arXiv:2605.26654v1 Announce Type: cross Abstract: Reinforcement learning (RL) often has a hierarchical structure, where an upper-level (UL) learner selects model parameters and a lower-level (LL) deci

BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma

arXiv:2605.26376v1 Announce Type: cross Abstract: Hepatocellular carcinoma (HCC) is biologically heterogeneous, shaped by the interplay between hepatic functional reserve and tumor-related oncologic f

tutorialsarxiv-cs-ai

Black-box Membership Inference Attacks on the Pre-training Data of Image-generation Models

arXiv:2605.27020v1 Announce Type: cross Abstract: The rapid advancement of diffusion-based image generation models has raised serious concerns regarding potential copyright and privacy infringements i

Boosting Knowledge Graph Foundation Models via Enhanced Negative Sampling

arXiv:2605.27023v1 Announce Type: new Abstract: Knowledge graphs (KGs) have become the core backbone of numerous downstream tasks such as question answering and recommender systems. However, despite a

Local Ai

Bounded Path Context: A Controlled Study of Visible Path History in LLM-Based Knowledge Graph Question Answering

arXiv:2605.26645v1 Announce Type: new Abstract: LLM-based knowledge-graph question answering (KGQA) delegates graph traversal to language models, turning each question into a sequence of local relatio

local-aiarxiv-cs-cl

Breaking the Epistemic Trap: Active Perception Under Compound Uncertainty

arXiv:2605.26627v1 Announce Type: cross Abstract: Deploying reinforcement learning in safety critical domains, from autonomous vehicles to medical decision support, is constrained by failures arising

safetyarxiv-cs-ro

BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenization

arXiv:2605.26182v1 Announce Type: new Abstract: Generating physically buildable brick structures from 3D shapes requires more than geometric reconstruction: the output must also satisfy discrete part

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection

arXiv:2605.26193v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) has long been a hot research topic in data mining due to its various applications. Recent studies challenge the e

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial

arXiv:2605.26577v1 Announce Type: cross Abstract: Learning-based methods for synthesizing controllers have gained popularity due to their high expressiveness and strong empirical performance. However,

BUILD with Precision: Bottom-Up Inference of Linear DAGs

arXiv:2512.16111v2 Announce Type: replace Abstract: Learning the structure of directed acyclic graphs (DAGs) from observational data is a central problem in causal discovery, statistical signal proces

researcharxiv-cs-lg

Agents

Can Broad Biomedical Knowledge be Contextualized into Scenario-Grounded Propositions?

arXiv:2605.27082v1 Announce Type: new Abstract: Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests rel

agentsarxiv-cs-ai

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

Agents

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

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

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

Applications

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

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

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

Applications

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

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

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

Agents

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

Applications

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

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