arXiv:2604.15719v2 Announce Type: new
Abstract: Many consequential decisions must be made before the relevant outcome is known. Such problems are commonly framed as future prediction, where an LLM agent must form a prediction for an unresolved questio…
arXiv:2604.16581v1 Announce Type: new
Abstract: Neural Combinatorial Optimization (NCO) has emerged as a powerful framework for solving combinatorial optimization problems by integrating deep learning-based models. This work focuses on improving exist…
arXiv:2604.17420v1 Announce Type: new
Abstract: Money laundering poses severe risks to global financial systems, driving the widespread adoption of machine learning for transaction monitoring. However, progress remains stifled by the lack of realistic…
arXiv:2604.18557v1 Announce Type: cross
Abstract: Controllable cooperative humanoid manipulation is a fundamental yet challenging problem for embodied intelligence, due to severe data scarcity, complexities in multi-agent coordination, and limited gen…
arXiv:2506.01732v2 Announce Type: replace
Abstract: Large Language Models (LLMs) are pre-trained on large data from different sources and domains. These datasets often contain trillions of tokens, including large portions of copyrighted or proprietary…
arXiv:2604.16841v1 Announce Type: new
Abstract: Land surface temperature (LST) super-resolution is important for environmental monitoring. However, it remains challenging as coarse thermal observations severely underdetermine fine-scale structure. In …
arXiv:2604.17306v1 Announce Type: new
Abstract: This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge aims to recover high-re…
arXiv:2505.19237v2 Announce Type: replace-cross
Abstract: Self-recognition — the ability to maintain an internal representation of one’s own body within the environment — underpins intelligent, autonomous behavior. As a foundational component of the…
arXiv:2506.05606v5 Announce Type: replace
Abstract: Can large language models (LLMs) accurately simulate the next web action of a specific user? While LLMs have shown promising capabilities in generating “believable” human behaviors, evaluating thei…
arXiv:2604.16586v1 Announce Type: new
Abstract: Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and biological behavior. This survey traces four complem…