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Carnegie Mellon University researchers are presenting 50 papers at EMNLP 2025, covering diverse NLP and ML topics including multimodal models, AI safety, reasoning capabilities, code generation, and human-AI interaction. The research spans theoretical advances in model interpretability and alignment, practical applications in chemistry and finance, and novel benchmarks for evaluating LLM performance across languages and domains. Key themes include inference-time scaling, retrieval-augmented generation, and interdisciplinary applications of language models.

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