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20 results
arxiv.org πŸ“… 2025 πŸ“° arXiv πŸ“„ PDF
Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation
πŸ‘€ Yifan Liu; Yaokun Liu; Zelin Li; Zhenrui Yue; Gyuseok Lee; Ruichen Yao; Yang Zhang; Dong Wang

Recent advances in generative recommenders adopt a two-stage paradigm: items are first tokenized into semantic IDs using a pretrained tokenizer, and then large language models (LLMs) are trained to generate the next item via sequence-to-sequence modeling. However, these two stages are optimized for different objectives…

cs.IR cs.AI cs.CL
arxiv.org πŸ“… 2001 πŸ“° arXiv πŸ“„ PDF
An Environment for the Exploration of Non Monotonic Logic Programs
πŸ‘€ Luis F. Castro; David S. Warren

Stable Model Semantics and Well Founded Semantics have been shown to be very useful in several applications of non-monotonic reasoning. However, Stable Models presents a high computational complexity, whereas Well Founded Semantics is easy to compute and provides an approximation of Stable Models. Efficient engines exi…

cs.PL cs.LO
arxiv.org πŸ“… 2025 πŸ“° arXiv πŸ“„ PDF
Saudi-Dialect-ALLaM: LoRA Fine-Tuning for Dialectal Arabic Generation
πŸ‘€ Hassan Barmandah

Large language models (LLMs) for Arabic are still dominated by Modern Standard Arabic (MSA), with limited support for Saudi dialects such as Najdi and Hijazi. This underrepresentation hinders their ability to capture authentic dialectal variation. Using a privately curated Saudi Dialect Instruction dataset (Hijazi and …

cs.CL cs.LG
arxiv.org πŸ“… 2025 πŸ“° arXiv πŸ“„ PDF
Silence is Not Consensus: Disrupting Agreement Bias in Multi-Agent LLMs via Catfish Agent for Clinical Decision Making
πŸ‘€ Yihan Wang; Qiao Yan; Zhenghao Xing; Lihao Liu; Junjun He; Chi-Wing Fu; Xiaowei Hu; Pheng-Ann Heng

Large language models (LLMs) have demonstrated strong potential in clinical question answering, with recent multi-agent frameworks further improving diagnostic accuracy via collaborative reasoning. However, we identify a recurring issue of Silent Agreement, where agents prematurely converge on diagnoses without suffici…

cs.CL cs.AI cs.LG q-bio.OT
arxiv.org πŸ“… 2025 πŸ“° arXiv πŸ“„ PDF
Semantic Web and Software Agents -- A Forgotten Wave of Artificial Intelligence?
πŸ‘€ Tapio PitkΓ€ranta; Eero HyvΓΆnen

The history of Artificial Intelligence (AI) is a narrative of waves -- rising optimism followed by crashing disappointments. AI winters, such as the early 2000s, are often remembered as barren periods of innovation. This paper argues that such a perspective overlooks a crucial wave of AI that seems to be forgotten: the…

cs.SI cs.CY cs.DL
arxiv.org πŸ“… 2024 πŸ“° arXiv πŸ“„ PDF
DeepFM-Crispr: Prediction of CRISPR On-Target Effects via Deep Learning
πŸ‘€ Condy Bao; Fuxiao Liu

Since the advent of CRISPR-Cas9, a groundbreaking gene-editing technology that enables precise genomic modifications via a short RNA guide sequence, there has been a marked increase in the accessibility and application of this technology across various fields. The success of CRISPR-Cas9 has spurred further investment a…

q-bio.QM cs.AI cs.LG
arxiv.org πŸ“… 2024 πŸ“° arXiv πŸ“„ PDF
CRISPR-GPT for Agentic Automation of Gene-editing Experiments
πŸ‘€ Yuanhao Qu; Kaixuan Huang; Ming Yin; Kanghong Zhan; Dyllan Liu; Di Yin; Henry C. Cousins; William A. Johnson; Xiaotong Wang; Mihir Shah; Russ B. Altman; Denny Zhou; Mengdi Wang; Le Cong

The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an efficient gene-editing system requires a deep understanding of CRISPR technology, and the complex experimental systems under investigation. While…

cs.AI cs.CL cs.HC q-bio.QM
arxiv.org πŸ“… 2025 πŸ“° arXiv πŸ“„ PDF
Redundancy-as-Masking: Formalizing the Artificial Age Score (AAS) to Model Memory Aging in Generative AI
πŸ‘€ Seyma Yaman Kayadibi

Artificial intelligence is observed to age not through chronological time but through structural asymmetries in memory performance. In large language models, semantic cues such as the name of the day often remain stable across sessions, while episodic details like the sequential progression of experiment numbers tend t…

cs.CL cs.AI cs.IT cs.LG
DOI: 10.3389/frai.2026.1732691
arxiv.org πŸ“… 2026 πŸ“° arXiv πŸ“„ PDF
Structural shifts in institutional participation and collaboration within the AI arXiv preprint research ecosystem
πŸ‘€ Shama Maganur; Mayank Kejriwal

The emergence of large language models (LLMs) represents a significant technological shift within the scientific ecosystem, particularly within the field of artificial intelligence (AI). This paper examines structural changes in the AI research landscape using a dataset of arXiv preprints (cs.AI) from 2021 through 2025…

cs.SI cs.AI
arxiv.org πŸ“… 2021 πŸ“° arXiv πŸ“„ PDF
Form 10-Q Itemization
πŸ‘€ Yanci Zhang; Tianming Du; Yujie Sun; Lawrence Donohue; Rui Dai

The quarterly financial statement, or Form 10-Q, is one of the most frequently required filings for US public companies to disclose financial and other important business information. Due to the massive volume of 10-Q filings and the enormous variations in the reporting format, it has been a long-standing challenge to …

cs.IR econ.GN q-fin.GN
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