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arXiv:2603.22985v1 Announce Type: new Abstract: Current multimodal toxicity benchmarks typically use a single binary hatefulness label. This coarse approach conflates two fundamentally different characteristics of …
arXiv:2603.22999v1 Announce Type: new Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, existing …
arXiv:2603.23013v1 Announce Type: new Abstract: Production AI agents frequently receive user-specific queries that are highly repetitive, with up to 47\% being semantically similar to prior …
arXiv:2603.23047v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) fine-tuning has shown substantial improvements over vanilla RAG, yet most studies target document question answering and often …
arXiv:2603.23069v1 Announce Type: new Abstract: The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning …
arXiv:2603.23091v1 Announce Type: new Abstract: While brain-aligned large language models (LLMs) have garnered attention for their potential as cognitive models and for potential for enhanced …
arXiv:2603.23136v1 Announce Type: new Abstract: Automated knowledge graph (KG) construction is essential for navigating the rapidly expanding body of scientific literature. However, existing approaches struggle …
arXiv:2603.23146v1 Announce Type: new Abstract: The widespread adoption of Large Language Models (LLMs) has made the detection of AI-Generated text a pressing and complex challenge. …
arXiv:2603.23160v1 Announce Type: new Abstract: Benchmarking AI systems in multi-turn interactive scenarios is essential for understanding their practical capabilities in real-world applications. However, existing evaluation …
arXiv:2603.23172v1 Announce Type: new Abstract: Multilingual intent classification is central to customer-service systems on global logistics platforms, where models must process noisy user queries across …
arXiv:2603.23184v1 Announce Type: new Abstract: Reward modeling represents a long-standing challenge in reinforcement learning from human feedback (RLHF) for aligning language models. Current reward modeling …
arXiv:2603.23219v1 Announce Type: new Abstract: Amidst the rising capabilities of generative AI to mimic specific human styles, this study investigates the ability of state-of-the-art large …