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Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, resources, and long-term consequences into executable and verifiable solutions. Existing…

Artificial Intelligence · Computer Science 2026-05-21 Ziliang Zhao , Zenan Xu , Shuting Wang , Hongjin Qian , Yan Lei , Minda Hu , Zhao Wang , Shihan Dou , Zhicheng Dou , Pluto Zhou

The use of spreadsheets is widespread. Be it in business, finance, engineering or other areas, spreadsheets are created for their flexibility and ease to quickly model a problem. Very often they evolve from simple prototypes to…

Software Engineering · Computer Science 2011-11-30 José Pedro Correia , Miguel A. Ferreira

Recently, there has been a growing interest among large language model (LLM) developers in LLM-based document reading systems, which enable users to upload their own documents and pose questions related to the document contents, going…

Computation and Language · Computer Science 2024-07-16 Anni Zou , Wenhao Yu , Hongming Zhang , Kaixin Ma , Deng Cai , Zhuosheng Zhang , Hai Zhao , Dong Yu

Generative AI and Large Language Models (LLMs) hold promise for automating spreadsheet formula creation. However, due to hallucinations, bias and variable user skill, outputs obtained from generative AI cannot be assumed to be accurate or…

Human-Computer Interaction · Computer Science 2025-01-20 Simon Thorne

The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a critical evaluation gap: established benchmarks focus on…

Large Language Models (LLMs) have achieved state-of-the-art performance on a broad range of Natural Language Processing (NLP) tasks, including document processing and code generation. Autoregressive Language Models (ARMs), which generate…

Large Language Models (LLMs) have emerged as a powerful tool in advancing the Text-to-SQL task, significantly outperforming traditional methods.Nevertheless, as a nascent research field, there is still no consensus on the optimal prompt…

Computation and Language · Computer Science 2026-03-20 Bin Zhang , Yuxiao Ye , Guoqing Du , Xiaoru Hu , Zhishuai Li , Chi Harold Liu , Zhiwei Xu , Guoliang Fan , Rui Zhao , Ziyue Li , Hangyu Mao

Although natural language is the default medium for Large Language Models (LLMs), its limited expressive capacity creates a profound bottleneck for complex problem-solving. While recent advancements in AI have relied heavily on scaling,…

Artificial Intelligence · Computer Science 2026-05-13 Zhiqin Yang , Yuhan Liu , Jingwen Fu , Pei Fu , Bo Han , Masashi Sugiyama , Nanning Zheng

TextArena is an open-source collection of competitive text-based games for training and evaluation of agentic behavior in Large Language Models (LLMs). It spans 57+ unique environments (including single-player, two-player, and multi-player…

Computation and Language · Computer Science 2025-05-27 Leon Guertler , Bobby Cheng , Simon Yu , Bo Liu , Leshem Choshen , Cheston Tan

Table processing, a key task in natural language processing, has significantly benefited from recent advancements in language models (LMs). However, the capabilities of LMs in table-to-text generation, which transforms structured data into…

Computation and Language · Computer Science 2024-10-18 Sahar Iravani , Tim . O . F Conrad

Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…

Computation and Language · Computer Science 2025-11-17 Fengxu Yang , Weitong Chen , Jack D. Evans

The rapid evolution of Large Language Models (LLMs) has fostered diverse paradigms for automated slide generation, ranging from code-driven layouts to image-centric synthesis. However, evaluating these heterogeneous systems remains…

Computation and Language · Computer Science 2026-01-15 Yunqiao Yang , Wenbo Li , Houxing Ren , Zimu Lu , Ke Wang , Zhiyuan Huang , Zhuofan Zong , Mingjie Zhan , Hongsheng Li

LLM leaderboards are widely used to compare models and guide deployment decisions. However, leaderboard rankings are shaped by evaluation priorities set by benchmark designers, rather than by the diverse goals and constraints of actual…

Artificial Intelligence · Computer Science 2026-04-24 Minji Jung , Minjae Lee , Yejin Kim , Sarang Choi , Minsuk Kahng

Engineering construction automation aims to transform natural language specifications into physically viable structures, requiring complex integrated reasoning under strict physical constraints. While modern LLMs possess broad knowledge and…

Artificial Intelligence · Computer Science 2026-05-20 Tian Xia , Tianrun Gao , Wenhao Deng , Long Wei , Xiaowei Qian , Chenglei Yu , Tailin Wu

Large Language Models (LLMs) have recently garnered significant attention, primarily for their capabilities in text-based interactions. However, natural human interaction often relies on speech, necessitating a shift towards voice-based…

Computation and Language · Computer Science 2025-08-08 Wenqian Cui , Dianzhi Yu , Xiaoqi Jiao , Ziqiao Meng , Guangyan Zhang , Qichao Wang , Yiwen Guo , Irwin King

The remarkable reasoning and generalization capabilities of Large Language Models (LLMs) have paved the way for their expanding applications in embodied AI, robotics, and other real-world tasks. To effectively support these applications,…

Computation and Language · Computer Science 2025-05-30 Dongil Yang , Minjin Kim , Sunghwan Kim , Beong-woo Kwak , Minjun Park , Jinseok Hong , Woontack Woo , Jinyoung Yeo

While Large Language Models (LLMs) can accelerate text-heavy tasks in alternative investment due diligence, a gap remains in their ability to accurately extract and reason over structured tabular data from complex financial spreadsheets.…

Artificial Intelligence · Computer Science 2026-03-10 Jan Ravnik , Matjaž Ličen , Felix Bührmann , Bithiah Yuan , Felix Stinson , Tanvi Singh

Large language models (LLMs) excel at solving problems with clear and complete statements, but often struggle with nuanced environments or interactive tasks which are common in most real-world scenarios. This highlights the critical need…

Large language models (LLMs) are rapidly replacing help forums like StackOverflow, and are especially helpful for non-professional programmers and end users. These users are often interested in data-centric tasks, such as spreadsheet…

Current methods for generating 3D scene layouts from text predominantly follow a declarative paradigm, where a Large Language Model (LLM) specifies high-level constraints that are then resolved by a separate solver. This paper challenges…