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Found 8 papers, 1 papers with code
TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs
We construct a hierarchical task tree encompassing 7 major areas covering over 200 categories and over 800 tasks, which covers diverse capabilities such as question answering, reasoning, multiturn dialogue, and text generation, to evaluate LLMs in a comprehensive and in-depth manner.
Modeling Linguistic and Personality Adaptation for Natural Language Generation
Previous work has shown that conversants adapt to many aspects of their partners{'} language.
Storytelling Agents with Personality and Adaptivity
Our results show that subjects are able to perceive the intended variation in extraversion between different virtual agents, independently of the story they are telling and the gender of the agent.
Inferring Narrative Causality between Event Pairs in Films
To understand narrative, humans draw inferences about the underlying relations between narrative events.
Inference of Fine-Grained Event Causality from Blogs and Films
Human understanding of narrative is mainly driven by reasoning about causal relations between events and thus recognizing them is a key capability for computational models of language understanding.
Unsupervised Induction of Contingent Event Pairs from Film Scenes
Human engagement in narrative is partially driven by reasoning about discourse relations between narrative events, and the expectations about what is likely to happen next that results from such reasoning.
A Corpus of Gesture-Annotated Dialogues for Monologue-to-Dialogue Generation from Personal Narratives
This paper presents a new corpus, the Story Dialogue with Gestures (SDG) corpus, consisting of 50 personal narratives regenerated as dialogues, complete with annotations of gesture placement and accompanying gesture forms.
