Biomedical research articles are mainly written for experts and often contain terms that are difficult for the general public to understand. Automated lay summarization has become a solution to make biomedical knowledge easier for patients and the public to understand. However, generating lay summaries from full-text a...
This work reviews data strategies across the training lifecycle and formulates them as policies that allocate a training budget over candidate examples, then divides methods by their decision granularity, model dependence, and temporal adaptivity, then compares their computational requirements and empirical support.
Yuan-Jian Xu, Jia-Ning Hao, Tian-Ze Sun et al.· 0 citations
Tokenization is a critical component of the language modeling pipeline, but it is poorly understood. Tokenizers can impact downstream performance, but there is currently mixed evidence about which tokenizer features predict a better language model without requiring a full training run. In this paper, we analyze approxi...
Antonio Lopardo, Luis Frentzen Salim, Shikhar Srivastava et al.· 0 citations
Reinforcement learning with verifiable rewards (RLVR) improves multimodal reasoning, but group-relative policy optimization broadcasts a single sequence-level advantage to every token of a response, although errors usually localize to a few decisive steps. Recent self-distilled variants refine credit with a teacher--st...
Yi-Ran Zhang, Han-Bo Huang, Jie-Lan Li et al.· 0 citations
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Addressed conditional memory provides a local surface for post-hoc knowledge injection, but a successful write need not transfer to a new question or preserve untargeted behavior. This study combines a controlled GPT-2 comparison with production-memory experiments on Qwen3.8-Flash-Next-FP8 and DeepSeek-V4.1-Flash. Newl...
Wei Gao, Cheng Tian, Ya-Wen Duan et al.· 1 citation
Reliable repository-level coding requires agents not only to generate correct code but also to preserve constraints and respond to tool feedback across long interactions. However, our diagnostic analysis shows that agents often fail to act on relevant information already available in context, while final Pass/Fail outc...
Yu-Jia Luo, Zhi-Yi Lai, Zi-Qi Miao et al.· 0 citations
Recent multilingual large language models achieve strong translation performance, yet the internal mechanisms responsible for low-resource multilingual translation remain insufficiently understood. In this paper, we study translation circuits in multilingual decoder-only LLMs for Hindi-to-Urdu and Hindi-to-Sindhi (Deva...
Atai Waris Khan, Abdullah Mazhar, R. Kumar et al.· Conference on Empirical Meth...· 0 citations
In automatic speech recognition (ASR), transcription errors with similar lexical or semantic discrepancies can have markedly different consequences for the situation conveyed by speech. Capturing these differences requires not merely contextual assessment, but an understanding of what the spoken discourse describes, es...
Ming-Zhe Lu, Jin-Hao Liu, Yun-Peng Li et al.· 0 citations
Early stress detection and risk prediction are crucial for timely mental health assessment and support. While large language models have recently shown promise for social media stress prediction, relying on accuracy can obscure false positives. Also, prompt revisions yield inconsistent gains across models and tasks, wi...
Seung-Jun Yi, Seung-Jun Yi, Sriram Sattiraju et al.· 0 citations
Mixture-of-Experts (MoE) models reduce computation by routing each token to a small set of experts, but each selected expert is still used at a fixed precision. We present DPA-MoE, a runtime precision control framework that makes routed experts any-precision. DPA-MoE encodes expert feed-forward weights as prefix-decoda...
Jaeyun Kim, Hoonki Lee, Su-Mi Shin et al.· Conference on Empirical Meth...· 0 citations
Residential design aims to transform existing homes into functional living spaces while satisfying diverse design preferences and physical constraints. However, existing floorplan generation methods typically assume empty building boundaries as input, whereas renovation requires reasoning over existing floorplans. Furt...
Jingguo Liu, Yuanqing Liu, Chong Zhang et al.· 0 citations
Large Language Models (LLMs) increasingly operate in multi-turn interactions that require maintaining latent conversational states, not only explicit facts. We study affective state as an implicit state inferred from sparse contextual cues that remain relevant after topic shifts, and ask whether LLMs expose internal at...
Wenqiu Tang, Zhen Wan, Yihui Wang et al.· 0 citations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
