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A peek into token bias: Large language models are not yet genuine reasoners
This study introduces a hypothesis-testing framework to assess whether large language
models (LLMs) possess genuine reasoning abilities or primarily depend on token bias. We …
models (LLMs) possess genuine reasoning abilities or primarily depend on token bias. We …
When Geoscience Meets Foundation Models: Toward a general geoscience artificial intelligence system
Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …
Multi-modal and multi-agent systems meet rationality: A survey
Rationality is characterized by logical thinking and decision-making that align with evidence
and logical rules. This quality is essential for effective problem-solving, as it ensures that …
and logical rules. This quality is essential for effective problem-solving, as it ensures that …
Towards Rationality in Language and Multimodal Agents: A Survey
Rationality is the quality of being guided by reason, characterized by decision-making that
aligns with evidence and logical principles. It plays a crucial role in reliable problem-solving …
aligns with evidence and logical principles. It plays a crucial role in reliable problem-solving …
Harnessing Large Language Models for Disaster Management: A Survey
Large language models (LLMs) have revolutionized scientific research with their exceptional
capabilities and transformed various fields. Among their practical applications, LLMs have …
capabilities and transformed various fields. Among their practical applications, LLMs have …
Pre-trained Graphformer-based Ranking at Web-scale Search
Both Transformer and Graph Neural Networks (GNNs) have been employed in the domain
of learning to rank (LTR). However, these approaches adhere to two distinct yet …
of learning to rank (LTR). However, these approaches adhere to two distinct yet …
Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale
Learning to rank (LTR) is widely employed in web searches to prioritize pertinent webpages
from retrieved content based on input queries. However, traditional LTR models encounter …
from retrieved content based on input queries. However, traditional LTR models encounter …