240 citations · 503 across the 31 of their papers we have counts for
5 papers · 1 filter
Do LLMs have Consistent Values?
Naama Rozen, Liat Bezalel, Gal Elidan +2
Large Language Models (LLM) technology is constantly improving towards human-like dialogue. Values are a basic driving force underlying human behavior, but little research has been…
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Avi Caciularu, Alon Jacovi, Eyal Ben-David +5
Large Language Models (LLMs) often do not perform well on queries that require the aggregation of information across texts. To better evaluate this setting and facilitate modeling…
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment
Roni Rabin, Alexandre Djerbetian, Roee Engelberg +4
Human communication often involves information gaps between the interlocutors. For example, in an educational dialogue, a student often provides an answer that is incomplete, and t…
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Paul Roit, Johan Ferret, Lior Shani +16
Despite the seeming success of contemporary grounded text generation systems, they often tend to generate factually inconsistent text with respect to their input. This phenomenon i…
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning
Deborah Cohen, Moonkyung Ryu, Yinlam Chow +8
Despite recent advances in natural language understanding and generation, and decades of research on the development of conversational bots, building automated agents that can carr…