arXiv AI
Jul 2
LLMs in the Real World: Evaluating "AI" in Emergency Contexts
arXiv:2607. 00019v1 Announce Type: cross Abstract: This paper offers a call to action.
LLM-Powered Automatic Translation and Urgency in Crisis Scenarios
arXiv:2602. 13452v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication.
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arXiv AI
Jul 23
On the Systematic Challenges of Culturally Loaded Machine Translation: Dream of the Red Chamber as the Cultural Lens
arXiv:2607. 20241v1 Announce Type: cross Abstract: Culturally loaded translation poses unique challenges for machine translation (MT), as meanings are deeply embedded in socio-cultural contexts beyond surface linguistic forms.
Hugging Face Trending Papers
Jun 8
Guide Me Out: A Framework to Benchmark VLM Operators Communication in Crisis Scenarios
Effective crisis response requires spatially grounded communication that bridges linguistic guidance of civilians with the physical environment, accounting for structural bottlenecks, evolving threats, and agent-specific contexts. Yet, current NLP research in crisis communication remains mainly limited to static, text-only classification settings, overlooking the critical communicative role of AI operators in dynamic, embodied scenarios.
arXiv AI
1d ago
LLM Safety Alignment in Low-Resource Languages: A Systematic Literature Review
arXiv:2608. 14626v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved substantial progress in safety alignment, yet their safety guarantees remain significantly weaker in low-resource and multilingual settings than in high-resource languages.
arXiv AI
Jun 10
Expert-Level Crisis Detection in Mental Health Conversations
arXiv:2606. 10380v1 Announce Type: cross Abstract: Real-world crisis intervention is inherently conversational, yet existing research largely focuses on static texts.
arXiv AI
Jul 3
SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses
arXiv:2607. 02049v1 Announce Type: cross Abstract: Large Language Models are increasingly deployed in emotional-support contexts and crisis-related situations.
arXiv AI
Jun 30
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
arXiv:2606. 28843v1 Announce Type: cross Abstract: Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task.
arXiv AI
Jun 9
Sycophancy as a Multilingual Alignment Failure: How Safety Degrades Across Languages, Topics, and Models
arXiv:2606. 08451v1 Announce Type: cross Abstract: Safety-aligned large language models often exhibit sycophancy, which is the tendency to affirm users' opinions regardless of factual accuracy.
arXiv AI
Jun 30
Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models
arXiv:2601. 05366v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed as agents that invoke external tools through structured function calls.
arXiv AI
Jun 2
TukaBench: A Culturally Grounded Jailbreak Benchmark for African Languages
arXiv:2606. 01322v1 Announce Type: cross Abstract: Safety evaluation of Large Language Models (LLMs) remains heavily English-centric, leaving Low-Resource Languages (LRLs), particularly African ones, critically underexplored.
arXiv AI
Jun 17
Translating the Untranslatable: An Operationalizable Ontology for Untranslatability
arXiv:2606. 17354v1 Announce Type: cross Abstract: Untranslatability, cases where meaning cannot be directly preserved across languages, is well-studied in linguistics but underexplored in NLP.
arXiv AI
Jun 16
CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment
arXiv:2606. 15396v1 Announce Type: cross Abstract: Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns.