Facilitating Cross-lingual Transfer of Empathy through Language-independent Latent Diffusion: A Case Study in C hinese (2025)

Abstract: Human empathy builds on the shared pragmatic common ground among different languages. However, existing human empathy data is limited to English. Inspired by multilingual coactivation as the neurocognitive underpinning of human bilingual proficiency, which predicts empathy, we integrate language-independent diffusion processes to facilitate the cross-lingual transfer of empathy. Taking Chinese language varieties as the target domain, automatic and human evaluations demonstrate successful transfers of source empathy into target contexts without compromising linguistic naturalness. The results of this work offer empirical clues on the importance of pragmatic transferability of empathy and its cross-lingual effects in conversation.

## introduction empathy, as "an other-oriented emotional response elicited by and congruent with the perceived welfare of someone else" @xcite , has been widely argued as part of "universal language" @xcite . however, human-written empathetic conversation data is predominantly recorded in english @xcite . such a data bias poses challenges to the expression of empathy in the context of language diversity and lays significance on knowledge about the cross-lingual transferability of empathy. surrounding the transferability of empathy has ignited a longstanding debate. existing studies point out that empathy is expressed in a similar pattern across typologically distant languages and cultures @xcite @xcite . more concretely, multilingual individuals typically show an empathy advantage compared to monolinguals @xcite , thus reflecting the common underlying proficiency (cup) @xcite . however, there are also enough reasons to believe that empathy is intransferable among cultures, as individuals from nuanced linguistic-cultural backgrounds may emphasize or regulate different dimensions of empathy @xcite @xcite . recently, neuro-cognitive studies provide invaluable insights about the cross-lingual transferability of empathy, especially how language-free processes underpin the successful cross-lingual transfer of empathy. specifically, high-proficiency human multilinguals exhibit cross-lingual coactivation in emotional language processing @xcite @xcite . since language models exhibit similar representation to the human brain, these insights make it worthy of discussion: do language-independent representations, acquired through contrastive representation learning @xcite , activate languageagnostic sense and facilitate the cross-lingual expression of empathy? as the majority of studies in human empathetic dialogues are also english-dominant, limited knowledge has been acquired about the connection between language and empathy. spoken as native and second languages by more than 1.2 billion people @xcite , chinese language varieties, including standard and non-standard varieties, have been providing rich knowledge in the field of inter-language pragmatics @xcite . however, none of the existing nlp studies provide human-written empathetic dialogue data in chinese language varieties. the lack of human empathy data calls into question whether the llm's empathy, as pragmatic competence, can be implicitly and acceptably learned from other languages. inspired by human bilingualism, we adopt a latent diffusion process to model human pragmatic transfer in decoder-based llms. through comprehensive evaluations in chinese conversations (mandarin and cantonese), the diffusion-tuned llms show a consistent advantage over prompt-based and prompt-tuned counterparts and achieve sota performance compared with recent psycho-counseling baselines in chinese. the major contribution of this study is summarized below: ## method multilingual coactivation facilitates the development of affective processing @xcite . to mimic this effect, we propose lisen-diff (language-independent sense diffusion) to model human-like pragmatic transfer from source language to target language. we integrate language-independent representations into a backbone transformer through language-free networks (see figure 2 ). within the language-independent space, we control the conversation style as default or empathy. ## analysis the results of automatic, human, and ablation studies offer empirical insights into the pragmatic transferability of empathy as well as its reliance on language-independent activation seized by the lisendiff module. to dig deeper, we conduct a comparative analysis to show how empathy is acquired in the language-independent space. ## conclusions this paper represents the first study that explores the pragmatic transferability of empathy. taking chinese language varieties as the field of experiments, we provide empirical clues on how empathy can be adequately and perceivably transferred across languages. the lisendiff framework, modeling language-independent knowledge of pragmatic choice, highlights the importance of language-independent networks in boosting the cross-lingual generalizability of languagedependent knowledge. by comparing the latent and explicit responses, we observe noticeable crosslingual overlap and differences in terms of the expression of empathy. :;%<<=:67+0 yes, full of memories! bcxkyz?[\]w^e:;+0 those past events may not be over yet. absolutely! s'_`%ab_`?nw0 when i see them, i feel like they are still there. c:tde%()*=ibpfeghw,ai/+jykd+tc)*l:mj`n o\]w0 that's it, old photos have such a strong power. so touching! i feel the same way! these photos always make us miss the past. , , , , , , figure 6: a case of mandarin conversation based on llama-3.1 model. !"#$%&'() ;pqr+@xmath0...help! i still haven't done a lot of homework, i'm so scared! z{|}%k~k~%ä"åçéñwöü+áàâikäéñ%ããww, please be nervous, take one step at a time and arrange your time reasonably. come on! there is still some time left before school starts. do it slowly. åypçå^åh5p00zéèêhp0 yeah…but it's a lot…don't know what to do… ëíìîï"%ñwóòôó|öewõúùûü%k~~ †°w¢£h% §• ¶ßw0 you can sort your tasks by category, doing the most difficult or urgent ones first. set small goals and complete them step by step. get enough rest and stay efficient.