Quality follows upgrading
All Articles
arXiv:2603.07111v1 Announce Type: new Abstract: The Werewolf Game is a communication game where players' reasoning and discussion skills are essential. In this study, we present …
arXiv:2603.07138v1 Announce Type: new Abstract: Emotion Recognition in Conversation (ERC) is critical for enabling natural human-machine interactions. However, existing methods predominantly employ categorical or dimensional …
arXiv:2603.07202v1 Announce Type: new Abstract: As Large Language Models (LLMs) transition into autonomous agentic roles, the risk of deception-defined behaviorally as the systematic provision of …
arXiv:2603.07238v1 Announce Type: new Abstract: Similarities between language representations derived from Self-Supervised Speech Models (S3Ms) have been observed to primarily reflect geographic proximity or surface …
arXiv:2603.07286v1 Announce Type: new Abstract: Global safety models exhibit strong performance across widely used benchmarks, yet their training data rarely captures the cultural and linguistic …
arXiv:2603.07330v1 Announce Type: new Abstract: This study examines the role of uncertainty estimation (UE) methods in multilingual text classification under noisy and non-topical conditions. Using …
arXiv:2603.07346v1 Announce Type: new Abstract: Noisy training data can significantly degrade the performance of language-model-based classifiers, particularly in non-topical classification tasks. In this study we …
arXiv:2603.07366v1 Announce Type: new Abstract: Many errors in student essays can be explained by influence from the native language (L1). L1 interference refers to errors …
arXiv:2603.07368v1 Announce Type: new Abstract: Biases in large language models (LLMs) often manifest as systematic distortions in associations between demographic attributes and professional or social …
arXiv:2603.07372v1 Announce Type: new Abstract: Quality Estimation (QE) is essential for assessing machine translation quality in reference-less settings, particularly for domain-specific and low-resource language scenarios. …
arXiv:2603.07392v1 Announce Type: new Abstract: LLMs operating in dynamic real-world contexts often encounter knowledge that evolves continuously or emerges incrementally. To remain accurate and effective, …
arXiv:2603.07445v1 Announce Type: new Abstract: Large language models (LLMs) often require fine-tuning (FT) to perform well on downstream tasks, but FT can induce safety-alignment drift …