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Towards a unified view of preference learning for large language models: A survey
Large Language Models (LLMs) exhibit remarkably powerful capabilities. One of the crucial
factors to achieve success is aligning the LLM's output with human preferences. This …
factors to achieve success is aligning the LLM's output with human preferences. This …
Financial knowledge large language model
Artificial intelligence is making significant strides in the finance industry, revolutionizing how
data is processed and interpreted. Among these technologies, large language models …
data is processed and interpreted. Among these technologies, large language models …
FactAlign: Long-form factuality alignment of large language models
Large language models have demonstrated significant potential as the next-generation
information access engines. However, their reliability is hindered by issues of hallucination …
information access engines. However, their reliability is hindered by issues of hallucination …
MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimization
As large language models (LLMs) are rapidly advancing and achieving near-human
capabilities, aligning them with human values is becoming more urgent. In scenarios where …
capabilities, aligning them with human values is becoming more urgent. In scenarios where …
Cognitive Biases in Large Language Models for News Recommendation
Despite large language models (LLMs) increasingly becoming important components of
news recommender systems, employing LLMs in such systems introduces new risks, such …
news recommender systems, employing LLMs in such systems introduces new risks, such …
KEIR@ ECIR 2025: The Second Workshop on Knowledge-Enhanced Information Retrieval
Pretrained language models (PLMs) like BERT and GPT-4 have become the foundation for
modern information retrieval (IR) systems. However, existing PLM-based IR models primarily …
modern information retrieval (IR) systems. However, existing PLM-based IR models primarily …