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Treatment, evidence, imitation, and chat

arXiv:2506.23040v4 Announce Type: replace-cross Abstract: Large language models are thought to have the potential to aid in medical decision making. This work investigates the degree to which this mig

TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs

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DGX agent

arXiv:2604.20043v1 Announce Type: cross Abstract: Explainability for Large Language Model (LLM) agents is especially challenging in interactive, partially observable settings, where decisions depend o

agentsarxiv-cs-ai

23 Apr 2026

Trust, Lies, and Long Memories: Emergent Social Dynamics and Reputation in Multi-Round Avalon with LLM Agents

arXiv:2604.20582v1 Announce Type: cross Abstract: We study emergent social dynamics in LLM agents playing The Resistance: Avalon, a hidden-role deception game. Unlike prior work on single-game perform

agentsarxiv-cs-ai

TTKV: Temporal-Tiered KV Cache for Long-Context LLM Inference

arXiv:2604.19769v1 Announce Type: cross Abstract: Key-value (KV) caching is critical for efficient inference in large language models (LLMs), yet its memory footprint scales linearly with context leng

UCCL-Zip: Lossless Compression Supercharged GPU Communication

arXiv:2604.17172v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) has made GPU communication a critical bottleneck. While prior work reduces communication volu

uLEAD-TabPFN: Uncertainty-aware Dependency-based Anomaly Detection with TabPFN

arXiv:2604.20255v1 Announce Type: cross Abstract: Anomaly detection in tabular data is challenging due to high dimensionality, complex feature dependencies, and heterogeneous noise. Many existing meth

Ultrafast Sampling-based Kinodynamic Planning via Differential Flatness

arXiv:2603.16059v2 Announce Type: replace Abstract: Motion planning under dynamics constraints, i.e, kinodynamic planning, enables safe robot operation by generating dynamically feasible trajectories

researcharxiv-cs-ro

Understanding Overparametrization in Survival Models through Interpolation

arXiv:2512.12463v3 Announce Type: replace-cross Abstract: Classical statistical learning theory predicts a U-shaped relationship between test loss and model capacity, driven by the bias-variance trade

safetyarxiv-cs-lg

Understanding the Staged Dynamics of Transformers in Learning Latent Structure

model-releasesarxiv-cs-lg

arXiv:2511.19328v2 Announce Type: replace Abstract: Language modeling has shown us that transformers can discover latent structure from context, but the dynamics of how they acquire different componen

UniCon3R: Contact-aware 3D Human-Scene Reconstruction from Monocular Video

arXiv:2604.19923v1 Announce Type: new Abstract: We introduce UniCon3R (Unified Contact-aware 3D Reconstruction), a unified feed-forward framework for online human-scene 4D reconstruction from monocula

researcharxiv-cs-cv

UniCVR: From Alignment to Reranking for Unified Zero-Shot Composed Visual Retrieval

arXiv:2604.20318v1 Announce Type: new Abstract: Composed image retrieval, multi-turn composed image retrieval, and composed video retrieval all share a common paradigm: composing the reference visual

Unlocking the Forecasting Economy: A Suite of Datasets for the Full Lifecycle of Prediction Market: [Experiments & Analysis]

arXiv:2604.20421v1 Announce Type: new Abstract: Prediction markets are markets for trading claims on future events, such as presidential elections, and their prices provide continuously updated signal

researcharxiv-cs-lg

Unveiling Uncertainty-Aware Autonomous Cooperative Learning Based Planning Strategy

arXiv:2510.11041v2 Announce Type: replace Abstract: In future intelligent transportation systems, autonomous cooperative planning (ACP), becomes a promising technique to increase the effectiveness and

agentsarxiv-cs-ro

Using Learning Theories to Evolve Human-Centered XAI: Future Perspectives and Challenges

arXiv:2604.19788v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems continue to grow in size and complexity, so does the difficulty of the quest for AI transparency. In a world of

Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech

arXiv:2604.19801v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. Ho

UVIO: An UWB-Aided Visual-Inertial Odometry Framework with Bias-Compensated Anchors Initialization

arXiv:2308.00513v2 Announce Type: replace Abstract: This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide r

safetyarxiv-cs-ro

V-tableR1: Process-Supervised Multimodal Table Reasoning with Critic-Guided Policy Optimization

arXiv:2604.20755v1 Announce Type: new Abstract: We introduce V-tableR1, a process-supervised reinforcement learning framework that elicits rigorous, verifiable reasoning from multimodal large language

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection

arXiv:2603.26842v2 Announce Type: replace-cross Abstract: Time series anomaly detection (TSAD) is essential for maintaining the reliability and security of IoT-enabled service systems. Existing method

applicationsarxiv-cs-ai

Variance Is Not Importance: Structural Analysis of Transformer Compressibility Across Model Scales

model-releasesarxiv-cs-lg

arXiv:2604.20682v1 Announce Type: new Abstract: We present a systematic empirical study of transformer compression through over 40 experiments on GPT-2 (124M parameters) and Mistral 7B (7.24B paramete

Verification of Machine Unlearning is Fragile

arXiv:2408.00929v2 Announce Type: replace Abstract: As privacy concerns escalate in the realm of machine learning, data owners now have the option to utilize machine unlearning to remove their data fr

safetyarxiv-cs-lg

veScale-FSDP: Flexible and High-Performance FSDP at Scale

arXiv:2602.22437v3 Announce Type: replace-cross Abstract: Fully Sharded Data Parallel (FSDP), also known as Zero Redundancy Optimizer (ZeRO), is widely used for large-scale model training, because of

Vibrotactile Preference Learning: Uncertainty-Aware Preference Learning for Personalized Vibration Feedback

arXiv:2604.20210v1 Announce Type: cross Abstract: Individual differences in vibrotactile perception underscore the growing importance of personalization as haptic feedback becomes more prevalent in in

Video-ToC: Video Tree-of-Cue Reasoning

arXiv:2604.20473v1 Announce Type: new Abstract: Existing Video Large Language Models (Video LLMs) struggle with complex video understanding, exhibiting limited reasoning capabilities and potential hal

Visual Reasoning through Tool-supervised Reinforcement Learning

arXiv:2604.19945v1 Announce Type: new Abstract: In this paper, we investigate the problem of how to effectively master tool-use to solve complex visual reasoning tasks for Multimodal Large Language Mo

agentsarxiv-cs-cv

Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly

arXiv:2604.20712v1 Announce Type: new Abstract: Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling s

safetyarxiv-cs-ro

VTouch++: A Multimodal Dataset with Vision-Based Tactile Enhancement for Bimanual Manipulation

arXiv:2604.20444v1 Announce Type: cross Abstract: Embodied intelligence has advanced rapidly in recent years; however, bimanual manipulation-especially in contact-rich tasks remains challenging. This

applicationsarxiv-cs-ai

Wan-Image: Pushing the Boundaries of Generative Visual Intelligence

arXiv:2604.19858v1 Announce Type: new Abstract: We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into p

applicationsarxiv-cs-cv

WebGen-R1: Incentivizing Large Language Models to Generate Functional and Aesthetic Websites with Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2604.20398v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic mul

Weighted Knowledge Distillation for Semi-Supervised Segmentation of Maxillary Sinus in Panoramic X-ray Images

arXiv:2604.20213v1 Announce Type: new Abstract: Accurate segmentation of maxillary sinus in panoramic X-ray images is essential for dental diagnosis and surgical planning; however, this task remains r

researcharxiv-cs-cv

What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization

arXiv:2601.17609v2 Announce Type: replace Abstract: In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that str

applicationsarxiv-cs-cl

What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity

arXiv:2604.19850v1 Announce Type: cross Abstract: Biological systems are promising substrates for computation because they naturally process environmental information through complex internal dynamics

researcharxiv-cs-lg

What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review

arXiv:2604.19998v1 Announce Type: new Abstract: Evaluating AI-generated reviews by verdict agreement is widely recognized as insufficient, yet current alternatives rarely audit which concerns a system

Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

arXiv:2604.20749v1 Announce Type: new Abstract: Situated conversational recommendation (SCR), which utilizes visual scenes grounded in specific environments and natural language dialogue to deliver co

Where are they looking in the operating room?

arXiv:2604.20574v1 Announce Type: new Abstract: Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studied in computer vision, advancing research in visual a

researcharxiv-cs-cv

Local Ai

Where Reasoning Breaks: Logic-Aware Path Selection by Controlling Logical Connectives in LLMs Reasoning Chains

arXiv:2604.20564v1 Announce Type: new Abstract: While LLMs demonstrate impressive reasoning capabilities, they remain fragile in multi-step logical deduction, where a single transition error can propa

local-aiarxiv-cs-cl

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment

arXiv:2601.14249v4 Announce Type: replace Abstract: Long chain-of-thought (CoT) trajectories provide rich supervision signals for distilling reasoning from teacher to student LLMs. However, both prior

safetyarxiv-cs-cl

White-Basilisk: A Hybrid Model for Code Vulnerability Detection

arXiv:2507.08540v5 Announce Type: replace-cross Abstract: The proliferation of software vulnerabilities presents a significant challenge to cybersecurity, necessitating more effective detection method

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives

arXiv:2604.20131v1 Announce Type: new Abstract: Increasingly, studies are exploring using Large Language Models (LLMs) for accelerated or scaled qualitative analysis of text data. While we can compare

safetyarxiv-cs-cl

Why AI-Generated Text Detection Fails: Evidence from Explainable AI Beyond Benchmark Accuracy

arXiv:2603.23146v2 Announce Type: replace-cross Abstract: The widespread adoption of Large Language Models (LLMs) has made the detection of AI-Generated text a pressing and complex challenge. Although

WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring

arXiv:2604.20190v1 Announce Type: new Abstract: Wildfire monitoring requires timely, actionable situational awareness from airborne platforms, yet existing aerial visual question answering (VQA) bench

WISCA: A Lightweight Model Transition Method to Improve LLM Training via Weight Scaling

arXiv:2508.16676v2 Announce Type: replace-cross Abstract: Transformer architecture gradually dominates the LLM field. Recent advances in training optimization for Transformer-based large language mode

researcharxiv-cs-cl

WorkflowGen:an adaptive workflow generation mechanism driven by trajectory experience

arXiv:2604.19756v1 Announce Type: cross Abstract: Large language model (LLM) agents often suffer from high reasoning overhead, excessive token consumption, unstable execution, and inability to reuse p

Working Memory Constraints Scaffold Learning in Transformers under Data Scarcity

arXiv:2604.20789v1 Announce Type: cross Abstract: We investigate the integration of human-like working memory constraints into the Transformer architecture and implement several cognitively inspired a

X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference

arXiv:2604.20289v1 Announce Type: new Abstract: Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Rec

agentsarxiv-cs-cv

X-IONet: Cross-Platform Inertial Odometry Network for Pedestrian and Legged Robot

arXiv:2511.08277v2 Announce Type: replace-cross Abstract: Learning-based inertial odometry has achieved remarkable progress in pedestrian navigation. However, extending these methods to quadruped robo

researcharxiv-cs-lg

X-PCR: A Benchmark for Cross-modality Progressive Clinical Reasoning in Ophthalmic Diagnosis

arXiv:2604.20350v1 Announce Type: new Abstract: Despite significant progress in Multi-modal Large Language Models (MLLMs), their clinical reasoning capacity for multi-modal diagnosis remains largely u

3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography

arXiv:2502.02779v3 Announce Type: replace-cross Abstract: Head computed tomography (CT) imaging is a widely-used imaging modality with multitudes of medical indications, particularly in assessing path

22 Apr 2026

A Bolu: A Structured Dataset for the Computational Analysis of Sardinian Improvisational Poetry