Chatbots are increasingly consulted about public affairs, and their judgments of policies are useful only if they are robust. We measure this robustness in the setting of an ordinary user, through consumer chat interfaces. For 30 days, five chatbot configurations (Mistral, Gemini Flash, Claude Sonnet, and Claude Opus a...
The capacity for uninterrupted, one-shot document parsing signifies a fundamental paradigm shift into the OCR 3.0 era, and enables document parsing over virtually unlimited lengths without prohibitive memory overhead.
Shubo Wei, Jing-Jing Wu, Qun-Yi Xie et al.· 0 citations
Large language models (LLMs) are increasingly used to generate research ideas from scientific literature. Existing systems combine literature retrieval with search, generation, and refinement, making it difficult to determine how the retrieval strategy itself shapes the ideas generated. We isolate this contribution by...
Zhipin Wang, Koel Dutta Chowdhury, Christoph Leiter et al.· 0 citations
Large language models (LLMs) are increasingly explored for mental health support, yet existing benchmarks primarily focus on supportive capabilities rather than whether models consistently adhere to professional ethical boundaries. This issue is particularly important in multi-turn interactions, where users may introdu...
Bi-Chen Wang, Yu-Feng Jin, Yi-Xin Sun et al.· 0 citations
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LLM-guided evolutionary search iteratively selects existing programs, uses LLMs as mutation operators to generate a new program, and evaluates it to guide subsequent search. To preserve diversity and reduce the risk of premature convergence, it often adopts the island model, in which groups of programs, called islands,...
Seockbean Song, Youngsik Yoon, Sungjae Lee et al.· 0 citations
Large language models hold promise for delivering safe, scientifically grounded, and personalized exercise guidance at scale, yet the sports-and-health domain still lacks curated training corpora and rigorous evaluation benchmarks. Keepace (Keepace.ai) is a domain-specialized LLM built on Qwen3.5-27B through post-train...
A metacognitive controller is introduced that guides diffusion generation according to the needs of the current response and the agent's interaction with the environment, reducing overall computation within responses.
Ming-Yu Zhao, Shu-Hang Lin, Li-Gong Han et al.· 0 citations
We study how text serialization affects table lookup in instruction-tuned language models. Our diagnostic asks the model to find the row containing a specified value under one named column, then return the value under another named column in that same row. We render the same synthetic 256-cell tables in row-major form...
This paper investigates whether the postmodern claim of unrestricted semantic indeterminacy, and its foundational Saussurean axiom of the arbitrary sign, are compatible with the structural architecture of Classical Arabic. We develop a formal mathematical model of Arabic non concatenative morphology in which lexical me...
This work presents the first evaluation of LLM imputation against proper multiple-imputation metrics and statistical baselines on more than 5 million imputed responses from four public opinion surveys under various missingness mechanisms and highlights the importance of fit-for-purpose evaluation for LLM imputation.
Tobias Holtdirk, Georg Ahnert, J. Sakshaug et al.· 2 citations
Experiments show that TextPro-SLM achieves the lowest modality gap among leading SLMs at both 3B and 7B scales, while also delivering strong overall performance on paralinguistic understanding tasks, suggesting that reducing the modality gap from the input side is both effective and data-efficient.
Wen-Qian Cui, Xiao-Hui Li, Da-Xin Tan et al.· arXiv.org· 3 citations
Autonomous agents powered by large language models (LLMs) perform complex tasks through long-horizon reasoning and tool interaction, where a fundamental trade-off arises between execution efficiency and reasoning robustness. Models at different capability-cost levels offer complementary advantages: lower-cost models en...
Wenbo Gao, Renxi Liu, Xian 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.