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arXiv:2605.26649v1 Announce Type: new Abstract: RGB-based imitation learning requires many demonstrations to generalize to unseen objects or scenes, motivating research into intermediate representatio

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Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization

DGX agent

arXiv:2602.00827v2 Announce Type: replace Abstract: Feature learning strength (FLS), i.e., the inverse of the effective output scaling of a model, plays a critical role in shaping the optimization dyn

safetyarxiv-cs-lg

27 May 2026

Pair-In, Pair-Out: Latent Multi-Token Prediction for Efficient LLMs

arXiv:2605.27255v1 Announce Type: cross Abstract: Long chain-of-thought reasoning has made autoregressive decoding the dominant inference cost of modern large language models. Existing methods target

Persona Generators: Generating Diverse Synthetic Personas for Arbitrary Contexts

arXiv:2602.03545v2 Announce Type: replace Abstract: Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative

PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization

arXiv:2507.16679v3 Announce Type: replace-cross Abstract: In-Context Learning has shown great potential for aligning Large Language Models (LLMs) with human values, helping reduce harmful outputs and

Probing Minimalist Phase Structure in LLMs: What Universal Dependencies Cannot Represent

arXiv:2605.26431v1 Announce Type: new Abstract: Structural probes train on Universal Dependencies (UD), which does not encode formal-syntactic abstractions such as phase boundaries or phase-internal c

Local Ai

Prototyping an End-to-End Multi-Modal Tiny-CNN for Cardiovascular Sensor Patches

arXiv:2510.18668v2 Announce Type: replace-cross Abstract: The vast majority of cardiovascular diseases may be preventable if early signs and risk factors are detected. Cardiovascular monitoring with b

local-aiarxiv-cs-cv

Q-GeoMem: Question-Guided Geometric Memory for Video Spatial Reasoning

arXiv:2605.27318v1 Announce Type: new Abstract: Video spatial reasoning requires accumulating viewpoint-dependent evidence over time while retaining information useful to the question being asked. Exi

researcharxiv-cs-cv

QAM-W: Joint 2D Codebook Quantization for LLM Weights via Hadamard Rotation and Activation-Aware Scaling

arXiv:2605.26339v1 Announce Type: cross Abstract: Scalar post-training quantizers discard pairwise coordinate structure within weight rows. We introduce QAM-W (Quadrature Amplitude Modulation for Weig

Hardware

Qrita: High-performance Top-k and Top-p using Pivot-based Truncation and Selection

arXiv:2602.01518v2 Announce Type: replace Abstract: Despite their importance in model sampling, efficient implementation of Top-k and Top-p algorithms for large vocabularies remains a significant chal

hardwarearxiv-cs-ai

Quantized Keys Steal Attention: Bias Correction for KV-Cache Compression in Video Diffusion

arXiv:2605.26266v1 Announce Type: cross Abstract: Chunk-wise autoregressive video diffusion models rely on a KV cache of previously generated chunks to avoid redundant computation, but this cache quic

Rethinking the Trust Region in LLM Reinforcement Learning

arXiv:2602.04879v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a cornerstone for fine-tuning Large Language Models (LLMs), with Proximal Policy Optimization (PPO) ser

Robust Koopman Control Barrier Filters for Safe Actor-Critic Reinforcement Learning

arXiv:2605.26452v1 Announce Type: cross Abstract: Safe reinforcement learning (RL) for robotic systems requires policies that improve task performance while satisfying state and input constraints duri

safetyarxiv-cs-lg

Local Ai

Source-Free Domain Adaptation for Geospatial Point Cloud Semantic Segmentation

arXiv:2601.08375v2 Announce Type: replace Abstract: Semantic segmentation of 3D geospatial point clouds is fundamental to remote sensing applications, yet domain shifts caused by regional and acquisit

local-aiarxiv-cs-cv

Structure-Adaptive Conformal Inference for Large-Scale Out-of-Distribution Testing

arXiv:2605.26429v1 Announce Type: cross Abstract: This paper addresses structured out-of-distribution (OOD) testing in high-stakes machine learning applications. Traditional conformal methods rely on

Stylistic Evolution and LLM Neutrality in Singlish Language

arXiv:2601.06580v2 Announce Type: replace Abstract: Singlish is a creole rooted in Singapore's multilingual environment that continues to evolve alongside social and technological change. We examine d

TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling

arXiv:2510.04533v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art image generation but often produce semantic inconsistencies, or hallucinations. Existing inference-time gu

researcharxiv-cs-cv

TailedCore: Few-Shot Sampling for Unsupervised Long-Tail Noisy Anomaly Detection

arXiv:2504.02775v2 Announce Type: replace Abstract: We aim to solve unsupervised anomaly detection in a practical challenging environment where the normal dataset is both contaminated with defective r

researcharxiv-cs-cv

Applications

TED: Related Party Transaction guided Tax Evasion Detection on Heterogeneous Graph

arXiv:2605.26984v1 Announce Type: new Abstract: Tax evasion causes severe losses of government revenues and disturbs the economic order of fair competition. To help alleviate this problem, the latest

applicationsarxiv-cs-lg

The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence

arXiv:2605.26494v1 Announce Type: new Abstract: We introduce the MiniMax-M2 series, a family of Mixture-of-Experts language models built around the principle that mini activations can unleash maximum

The Rescue Effect: Spatio-Semantic Early Exit Bypasses Quantization Collapse in CLIP

arXiv:2605.26415v1 Announce Type: cross Abstract: Deploying Vision-Language Models on resource-constrained hardware typically requires INT8 quantization, but in joint-embedding architectures such as C

Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction

arXiv:2505.11063v3 Announce Type: replace Abstract: LLM-based agents solve complex tasks through iterative reasoning, tool use, and environment interaction, where each intermediate thought directly sh

Towards Drone-based Mapping of Volcanic Gases using Gas Tomography

arXiv:2605.27180v1 Announce Type: new Abstract: Volcanoes emit large amounts of CO2, directly influencing human lives. Mapping volcanic gas emissions helps to forecast eruptions and understand the imp

researcharxiv-cs-ro

Tutorials

Towards Just-in-Time Adaptive Feedback: Enhancing Student Learning via Knowledge-Grounded LLM

arXiv:2605.26405v1 Announce Type: new Abstract: Educational interventions are effective tools for enhancing student learning. While Large Language Models (LLMs) allow for generating adaptive feedback

tutorialsarxiv-cs-cl

TPS-Drive: Task-Guided Representation Purification for VLM-based Autonomous Driving

arXiv:2605.27038v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide a promising foundation for autonomous driving planning, yet bridging semantic reasoning and precise 3D spatial for

safetyarxiv-cs-ro

Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules

arXiv:2605.26470v1 Announce Type: new Abstract: Generative posterior sampling using diffusion models has emerged as a dominant paradigm for solving inverse problems in imaging, which usually consists

safetyarxiv-cs-cv

Understanding the Challenges in Iterative Generative Optimization with LLMs

arXiv:2603.23994v2 Announce Type: replace-cross Abstract: Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using executio

Verilog-Evolve: Feedback-Driven and Skill-Evolving Verilog Generation

arXiv:2605.26498v1 Announce Type: new Abstract: Large language models (LLMs) have improved Verilog generation from natural-language specifications, but most pipelines still treat generation as isolate

When Eyes Betray AI: Social Gaze Consistency as a Semantic Cue for AI-Generated Image Detection

arXiv:2605.27348v1 Announce Type: cross Abstract: Recent generative models have largely closed the gap on low-level artifacts - pixel fingerprints, frequency anomalies, upsampling traces - particularl

A Formal gatekeeper Framework for Safe Dual Control with Active Exploration

arXiv:2510.06351v2 Announce Type: replace Abstract: Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations

safetyarxiv-cs-ro

A Multimodal Framework for Dementia Detection via Linguistic and Acoustic Representation Learning

arXiv:2605.25540v1 Announce Type: cross Abstract: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, an

safetyarxiv-cs-lg

A Token/KV-Cache Communication Media Selection and Resource Allocation Strategy for Multi-Agent Collaboration

arXiv:2605.25422v1 Announce Type: cross Abstract: The convergence of large language models (LLMs) with 6G networks is fostering a paradigm of autonomous multi-agent cooperation, which in turn is expec

Abduction-Deduction Entanglement: Domain Generalization via Representation Transplants

arXiv:2605.25156v1 Announce Type: cross Abstract: Prediction models trained under the source distribution do not generalize well to a different target distribution. A valid inference about an unseen d

Adversarial Orthogonal Disentanglement for LVLM Hallucination Mitigation

arXiv:2605.25377v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have advanced multimodal understanding, yet their reliability is limited by hallucination, where generated conten

Agent-as-Peer-Debriefer: A Multi-Agent Framework with Perspective-Based Refinement for Qualitative Analysis

arXiv:2605.24600v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for qualitative data analysis (QDA), yet their outputs often miss the depth and nuance of human analy

Agent-ToM: Learning to Monitor Autonomous LLM Agents via Theory-of-Mind Reasoning

arXiv:2605.24216v1 Announce Type: cross Abstract: Monitoring autonomous large language model (LLM) agents for covert malicious behavior is challenging due to delayed, context-dependent, and long-horiz

AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning

arXiv:2605.24486v1 Announce Type: new Abstract: Recent progress on long-horizon agentic tasks has been driven largely by scaling up individual agents through stronger models, better tools, and more ef

AGI Requires a Coordination Layer on Top of Pattern Repositories

arXiv:2512.05765v2 Announce Type: replace Abstract: In this paper we argue that influential critiques dismissing Large Language Models (LLMs) as a dead end for AGI misidentify the bottleneck: they con

ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering

arXiv:2011.10331v4 Announce Type: replace-cross Abstract: Multi-view clustering has wide applications in many image processing scenarios. In these scenarios, original image data often contain missing

researcharxiv-cs-lg

Approximating the universal thermal climate index using sparse regression with orthogonal polynomials

arXiv:2508.11307v3 Announce Type: replace-cross Abstract: The Universal Thermal Climate Index (UTCI) is a measure of thermal comfort that quantifies how humans experience environmental conditions. Due

researcharxiv-cs-lg

Associations between echocardiographic traits and AI-ECG predictions of heart failure

arXiv:2605.24576v1 Announce Type: new Abstract: Artificial intelligence-enabled electrocardiography (AI-ECG) can detect heart failure (HF), including disease not captured by left ventricular ejection

Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems

arXiv:2605.24458v1 Announce Type: cross Abstract: The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sector

Benchmarking non-conformity score functions in conformal prediction

arXiv:2605.24983v1 Announce Type: new Abstract: Conformal prediction is a useful and versatile alternative to model calibration in machine learning classification. It replaces single-class prediction

researcharxiv-cs-lg

Beyond the Proxy: Trajectory-Distilled Guidance for Offline GFlowNet Training

arXiv:2505.20110v3 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) excel at sampling diverse, high-reward objects. In many practical applications where active reward querie

Blocked Gibbs meets Diffusion Transformers: Unsupervised Learning for Constraint Optimization

arXiv:2605.25129v1 Announce Type: new Abstract: Diffusion models have shown promise in learning to solve constraint optimization problems. However, they are mostly restricted to problems with binary v

safetyarxiv-cs-lg

Applications

CAFD: Concept-Aware DNN Fault Detection using VLMs

arXiv:2605.24008v1 Announce Type: new Abstract: Fault detection for Deep Neural Networks (DNNs) has received increasing attention in recent years. While more advanced hybrid approaches have been propo

applicationsarxiv-cs-lg

CARL-CXR: Continual Adapter-Based Routing for Task-Unknown Chest Radiograph Classification

arXiv:2602.15811v2 Announce Type: replace-cross Abstract: Clinical deployment of chest radiograph classifiers requires models that can be updated as new datasets become available without retraining on

Catching The Correct Answer Trap: Characterising AI Tutor Blind Spots When Analysing Student Reasoning

arXiv:2605.23925v1 Announce Type: cross Abstract: Intelligent tutoring systems increasingly provide automated feedback on student work, but robust feedback requires assessing reasoning, not only final