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:2602.06221v2 Announce Type: replace
Abstract: Multiple-choice question answering (MCQA) is standard in NLP, but benchmarks lack rigorous quality control. We present BenchMarker, an education-inspired toolkit using LLM judges to flag three common…
arXiv:2505.23941v4 Announce Type: replace
Abstract: Large language models (LLMs) memorize a vast amount of prior knowledge from the Internet that helps them on downstream tasks but also may notoriously sway their outputs towards wrong or biased answer…
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:2604.16665v1 Announce Type: new
Abstract: Urgent blood donation seeking posts and messages on social media often go unnoticed due to the overwhelming volume of daily communications. Traditional app-based systems, reliant on manual input, struggl…
arXiv:2604.16813v1 Announce Type: cross
Abstract: Agentic AI systems are rapidly advancing toward real-world applications, yet their readiness in complex and personalized environments remains insufficiently characterized. To address this gap, we intro…
arXiv:2604.10321v2 Announce Type: replace
Abstract: In this paper, we review the NTIRE 2026 challenge on single-image reflection removal (SIRR) in the wild. SIRR is a fundamental task in image restoration. Despite progress in academic research, most m…
arXiv:2510.06133v2 Announce Type: replace
Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising. In commonly adopted parallel decoding schemes, each step confirms only high-confidence positions while remasking the…
arXiv:2510.05336v2 Announce Type: replace
Abstract: Historical archives on weather events are collections of enduring primary source records that offer rich, untapped narratives of how societies have experienced and responded to extreme weather events…
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…