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arXiv:2602.20647v1 Announce Type: new Abstract: I introduce semantic novelty--cosine distance between each paragraph's sentence embedding and the running centroid of all preceding paragraphs--as an information-theoretic …
arXiv:2602.20648v1 Announce Type: new Abstract: Client perceptions of the therapeutic alliance are critical for counseling effectiveness. Accurately capturing these perceptions remains challenging, as traditional post-session …
arXiv:2602.20670v1 Announce Type: new Abstract: Reward models play a fundamental role in aligning large language models with human preferences. Existing methods predominantly follow two paradigms: …
arXiv:2602.20727v1 Announce Type: new Abstract: LoRA has become a universal Parameter-Efficient Fine-Tuning (PEFT) technique that equips Large Language Models (LLMs) to adapt quickly to new …
arXiv:2602.20743v1 Announce Type: new Abstract: Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation varies with the …
arXiv:2602.20749v1 Announce Type: new Abstract: Natural Language Processing enables computers to understand human language by analysing and classifying text efficiently with deep-level grammatical and semantic …
arXiv:2602.20759v1 Announce Type: new Abstract: Existing alignment paradigms remain limited in capturing the pluralistic nature of human values. Overton Pluralism addresses this gap by generating …
arXiv:2602.20816v1 Announce Type: new Abstract: The core learning signal used in language model distillation is the standard Kullback-Leibler (KL) divergence between the student and teacher …
arXiv:2602.20859v1 Announce Type: new Abstract: Financial prediction from long documents involves significant challenges, as actionable signals are often sparse and obscured by noise, and the …
arXiv:2602.20892v1 Announce Type: new Abstract: Today, Social networks such as Twitter are the most widely used platforms for communication of people. Analyzing this data has …
arXiv:2602.20945v1 Announce Type: new Abstract: Large Language Models (LLMs) consistently benefit from scaled Chain-of-Thought (CoT) reasoning, but also suffer from heavy computational overhead. To address …
arXiv:2602.20966v1 Announce Type: new Abstract: This article describes a novel language task, the Blackbird Language Matrices (BLM) task, inspired by intelligence tests, and illustrates the …