arXiv Machine Learning
Jun 19
Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis
arXiv:2606. 19966v1 Announce Type: cross Abstract: Whole-slide images (WSIs) are widely used for computational cancer prognosis.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv Machine Learning
Jun 19
Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
arXiv:2510. 08807v2 Announce Type: replace-cross Abstract: From loco-motion to dextrous manipulation, humanoid robots have made remarkable strides in demonstrating complex full-body capabilities.
arXiv AI
Jun 19
ROSE: Benchmarking the Perception-to-Action Gap in Multimodal Models
arXiv:2606. 19965v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly expected to act on visual information, yet the same scene may require different actions under different task contexts.
arXiv Machine Learning
Jun 19
GEMS: Geometric Constraints Enable Multi-Semantic Superposition in LLMs
arXiv:2606. 19946v1 Announce Type: cross Abstract: Activation steering controls model behavior by modifying intermediate hidden states at inference time without retraining.
arXiv AI
Jun 19
GDGU: A Gradient Difference-based Graph Unlearning Method for Cyberattack Localization in Electric Vehicle Charging Networks
arXiv:2606. 19566v1 Announce Type: cross Abstract: Electric vehicle charging stations (EVCSs) can expose distribution feeders to cyberattacks.
arXiv Machine Learning
Jun 19
Predicting gestational age at birth in the context of preterm birth from multi-modal fetal MRI
arXiv:2606. 20172v1 Announce Type: new Abstract: Preterm birth is associated with significant mortality and a risk for lifelong morbidity.
arXiv AI
Jun 19
Trustworthy Multi-Agent Systems: Mitigating Semantic Drift with the Argent Signaling Protocol
arXiv:2606. 19356v1 Announce Type: cross Abstract: When multi-agent LLM systems produce bad answers, not all failures are equal: some answers are grounded in the right material but incomplete, while others are simply ungrounded and should be stopped.
arXiv AI
Jun 19
CogniFold: Always-On Proactive Memory via Cognitive Folding
arXiv:2605. 13438v3 Announce Type: replace Abstract: Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cognitive structure.
arXiv AI
Jun 19
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
arXiv:2506. 14990v3 Announce Type: replace Abstract: Benchmarks play a central role in reinforcement learning (RL) research, yet their computational constraints often shape what is studied.
arXiv AI
Jun 19
SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
arXiv:2606. 19755v1 Announce Type: cross Abstract: Speculative inference accelerates large language model (LLM) decoding but provides no inherent safety guarantees.
arXiv AI
Jun 19
UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
arXiv:2501. 17015v2 Announce Type: replace Abstract: Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect.
arXiv Machine Learning
Jun 19
DADP: Domain Adaptive Diffusion Policy
arXiv:2602. 04037v3 Announce Type: replace Abstract: Learning domain adaptive policies that can generalize to unseen transition dynamics, remains a fundamental challenge in learning-based control.
arXiv AI
Jun 19
Zero-Inflated Gaussian Distributions Enable Parameter-Space Sparsity in Estimation-of-Distribution Algorithms
arXiv:2606. 19369v1 Announce Type: cross Abstract: Estimation-of-distribution algorithms (EDAs) are a powerful class of evolutionary methods for black-box optimization, especially when little is known about the structure of the objective.
arXiv AI
Jun 19
TerraMind: Large-Scale Generative Multimodality for Earth Observation
arXiv:2504. 11171v5 Announce Type: replace-cross Abstract: We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO).
arXiv AI
Jun 19
Which Pairs to Compare for LLM Post-Training?
arXiv:2606. 19607v1 Announce Type: new Abstract: Preference-based post-training has become a central paradigm for aligning language models.
arXiv AI
Jun 19
QueryGaussian: Scalable and Training-Free Open-Vocabulary 3D Instance Retrieval
arXiv:2606. 19733v1 Announce Type: cross Abstract: Efficiently retrieving specific 3D instances from large-scale scenes via natural language prompts remains a formidable challenge in multimedia analysis.
arXiv AI
Jun 19
Multi-View Decompilation for LLM-Based Malware Classification
arXiv:2606. 20436v1 Announce Type: cross Abstract: Malware analysts often inspect compiled binaries through decompiled pseudo-C, when source code is unavailable.
arXiv AI
Jun 19
A Tool for the Synthesis of Adaptive Probabilistic Processors Based on the Ising Model
arXiv:2606. 19533v1 Announce Type: cross Abstract: This work presents a tool for the synthesis and simulation of probabilistic architectures for solving combinatorial optimization problems by mapping them to the Ising model.
arXiv Machine Learning
Jun 19
Kolmogorov-Arnold Reservoir Computing
arXiv:2606. 19984v1 Announce Type: new Abstract: Reservoir computing offers a lightweight framework for forecasting dynamical systems but may struggle to capture long-range dependencies due to limited representational capacity.
arXiv AI
Jun 19
NRITYAM: Language Models Meet Art and Heritage of Dance
arXiv:2606. 19727v1 Announce Type: cross Abstract: Language models have become essential tools in shaping modern workflows.