Zobrazeno 1 - 10
of 44
pro vyhledávání: '"FLek, Lucie"'
With the success of ChatGPT and other similarly sized SotA LLMs, claims of emergent human like social reasoning capabilities, especially Theory of Mind (ToM), in these models have appeared in the scientific literature. On the one hand those ToM-capab
Externí odkaz:
http://arxiv.org/abs/2410.06271
Recent advances in large language model (LLM) pruning have shown state-of-the-art compression results in post-training and retraining-free settings while maintaining high predictive performance. However, such research mainly considers calibrating pru
Externí odkaz:
http://arxiv.org/abs/2408.14398
Autor:
Nie, Shangrui, Fromm, Michael, Welch, Charles, Görge, Rebekka, Karimi, Akbar, Plepi, Joan, Mowmita, Nazia Afsan, Flores-Herr, Nicolas, Ali, Mehdi, Flek, Lucie
While preliminary findings indicate that multilingual LLMs exhibit reduced bias compared to monolingual ones, a comprehensive understanding of the effect of multilingual training on bias mitigation, is lacking. This study addresses this gap by system
Externí odkaz:
http://arxiv.org/abs/2407.05740
Autor:
Sotolar, Ondrej, Formanek, Vojtech, Debnath, Alok, Lahnala, Allison, Welch, Charles, FLek, Lucie
Empathetic response generation is a desirable aspect of conversational agents, crucial for facilitating engaging and emotionally intelligent multi-turn conversations between humans and machines. Leveraging large language models for this task has show
Externí odkaz:
http://arxiv.org/abs/2406.19071
Identifying user's opinions and stances in long conversation threads on various topics can be extremely critical for enhanced personalization, market research, political campaigns, customer service, conflict resolution, targeted advertising, and cont
Externí odkaz:
http://arxiv.org/abs/2406.16833
This paper addresses debiasing in news editing and evaluates the effectiveness of conversational Large Language Models in this task. We designed an evaluation checklist tailored to news editors' perspectives, obtained generated texts from three popul
Externí odkaz:
http://arxiv.org/abs/2404.06488
Autor:
Sarumi, Olufunke O., Neuendorf, Béla, Plepi, Joan, Flek, Lucie, Schlötterer, Jörg, Welch, Charles
Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual perspectives, particularly in subjective tasks. In scenarios where anno
Externí odkaz:
http://arxiv.org/abs/2404.02340
Recent language models have been improved by the addition of external memory. Nearest neighbor language models retrieve similar contexts to assist in word prediction. The addition of locality levels allows a model to learn how to weight neighbors bas
Externí odkaz:
http://arxiv.org/abs/2311.00475
The potential to provide patients with faster information access while allowing medical specialists to concentrate on critical tasks makes medical domain dialog agents appealing. However, the integration of large-language models (LLMs) into these age
Externí odkaz:
http://arxiv.org/abs/2308.14641
When searching for products, the opinions of others play an important role in making informed decisions. Subjective experiences about a product can be a valuable source of information. This is also true in sales conversations, where a customer and a
Externí odkaz:
http://arxiv.org/abs/2308.04226