Distilling Literary Sentiment from LLM Annotations into an Ordinal BERT Model

YesterdayReported by arXiv35

Distilling Literary Sentiment from LLM Annotations into an Ordinal BERT Model. The story centres on Gemma. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.

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Gemmamodel

Reported by arXiv

First seen yesterday

arXivDistilling Literary Sentiment from LLM Annotations into an Ordinal BERT ModelYesterdayArtem Suslov

AI Tools24

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation. It centres on Benchmarks, and also names Ollama and Phi. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Models — the section covering applications people use — assistants, editors, search, productivity.

arXiv22 Sept 2026

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Forty Questions: Identifying a Language Model from One-Word Answers

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Distilling Literary Sentiment from LLM Annotations into an Ordinal BERT Model

Companies, models and people in this story

Reported by arXiv

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Forty Questions: Identifying a Language Model from One-Word Answers

MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

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Companies, models and people in this story

Reported by arXiv

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MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

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