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arXiv:2603.04429v1 Announce Type: new Abstract: Current Large Language Model (LLM) preference learning methods such as Proximal Policy Optimization and Direct Preference Optimization learn from direct …
arXiv:2603.04452v1 Announce Type: new Abstract: To advance foundation Large Language Models (LLMs) for combustion science, this study presents the first end-to-end framework for developing domain-specialized …
arXiv:2603.04453v1 Announce Type: new Abstract: The use of multimodal large language models has become widespread, and as such the study of these models and their …
arXiv:2603.04454v1 Announce Type: new Abstract: How carefully and unambiguously a question is phrased has a profound impact on the quality of the response, for Language …
arXiv:2603.04592v1 Announce Type: new Abstract: Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in dynamic, …
arXiv:2603.04597v1 Announce Type: new Abstract: Large language models (LLMs) typically receive diverse natural language (NL) feedback through interaction with the environment. However, current reinforcement learning …
arXiv:2603.04647v1 Announce Type: new Abstract: Retrieval augmented generation mitigates limitations of large language models in factual consistency and knowledge updating by introducing external knowledge. However, …
arXiv:2603.04656v1 Announce Type: new Abstract: With the emergence of search-enabled generative QA systems, users are increasingly turning to tools that browse, aggregate, and reconcile evidence …
arXiv:2603.04657v1 Announce Type: new Abstract: Discussions of AI in education focus predominantly on student-facing tools -- chatbots, tutors, and problem generators -- while the potential …
arXiv:2603.04678v1 Announce Type: new Abstract: Large language models are known to often exhibit inconsistent knowledge. This is particularly problematic in multilingual scenarios, where models are …
arXiv:2603.04691v1 Announce Type: new Abstract: Stopwords are words that are not very informative to the content or the meaning of a language text. Most stopwords …
arXiv:2603.04698v1 Announce Type: new Abstract: This paper evaluates data augmentation and feature enhancement techniques for hate speech detection, comparing traditional classifiers, e.g., Delta Term Frequency-Inverse …