Quality follows upgrading
All Articles
arXiv:2603.18019v1 Announce Type: new Abstract: Do language model benchmarks actually measure what practitioners intend them to ? High-level metadata is too coarse to convey the …
arXiv:2603.18353v1 Announce Type: new Abstract: Language models encode task-relevant knowledge in internal representations that far exceeds their output performance, but whether mechanistic interpretability methods can …
arXiv:2603.18330v1 Announce Type: new Abstract: Persistent Large Language Model (LLM) agents expose a critical governance gap in memory management. Standard Retrieval-Augmented Generation (RAG) frameworks treat …
arXiv:2603.18676v1 Announce Type: new Abstract: MANAR (Memory-augmented Attention with Navigational Abstract Conceptual Representation), contextualization layer generalizes standard multi-head attention (MHA) by instantiating the principles of …
arXiv:2603.18614v1 Announce Type: new Abstract: Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound this interplay …
arXiv:2603.18382v1 Announce Type: new Abstract: Anonymization is widely treated as a practical safeguard because re-identifying anonymous records was historically costly, requiring domain expertise, tailored algorithms, …
arXiv:2603.18627v1 Announce Type: new Abstract: Precise Text-to-Image (T2I) generation has achieved great success but is hindered by the limited relational reasoning of static text encoders …
arXiv:2603.18420v1 Announce Type: new Abstract: Embedding models group text by semantic content, what text is about. We show that temporal co-occurrence within texts discovers a …
arXiv:2603.18294v1 Announce Type: new Abstract: Background: Clinical trials rely on transparent inclusion criteria to ensure generalizability. In contrast, benchmarks validating health-related large language models (LLMs) …
arXiv:2603.18008v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for mental-health support; yet prevailing evaluation methods--fluency metrics, preference tests, and generic dialogue …
arXiv:2603.18767v1 Announce Type: new Abstract: Concept unlearning has emerged as a promising direction for reducing the risks of harmful content generation in text-to-image diffusion models …
arXiv:2603.18124v1 Announce Type: new Abstract: Gender-based violence (GBV) is a major public health issue, with the World Health Organization estimating that one in three women …