SciAgent: Tool-augmented Language Models for Scientific Reasoning
On the map: LLM reasoning → Knowledge- and tool-augmented reasoning
also in 1 more
Abstract (arXiv)
Scientific reasoning poses an excessive challenge for even the most advanced Large Language Models (LLMs). To make this task more practical and solvable for LLMs, we introduce a new task setting named tool-augmented scientific reasoning. This setting supplements LLMs with scalable toolsets, and shifts the focus from pursuing an omniscient problem solver to a proficient tool-user. To facilitate the research of such setting, we construct a tool-augmented training corpus named MathFunc which encompasses over 30,000 samples and roughly 6,000 tools. Building on MathFunc, we develop SciAgent to retrieve, understand and, if necessary, use tools for scientific problem solving. Additionally, we craft a benchmark, SciToolBench, spanning five scientific domains to evaluate LLMs' abilities with tool assistance. Extensive experiments on SciToolBench confirm the effectiveness of SciAgent. Notably, SciAgent-Mistral-7B surpasses other LLMs with the same size by more than 13% in absolute accuracy. Furthermore, SciAgent-DeepMath-7B shows much superior performance than ChatGPT.
Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 36 of its 72 references that are in the map. First posted on arXiv 18 Feb 2024.
Builds on
36 of 72 references.
References · 36
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
- 2020Measuring Massive Multitask Language Understandingcited by 7,768
- 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
- 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,203
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
- 2019The Curious Case of Neural Text Degenerationcited by 2,881
- 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
- 2023Code Llama: Open Foundation Models for Codecited by 2,105
- 2023MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIcited by 2,044
- 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
24 more
- 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,449
- 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,302
- 2021Unsupervised Dense Information Retrieval with Contrastive Learningcited by 1,203
- 2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,154
- 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,057
- 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 751
- 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Modelscited by 694
- 2023WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instructcited by 618
- 2023MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuningcited by 483
- 2023Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoningcited by 379
- 2023Large Language Models as Tool Makerscited by 293
- 2023MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedbackcited by 293
- 2021ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learningcited by 253
- 2023GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructioncited by 245
- 2023ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddingscited by 238
- 2023TheoremQA: A Theorem-driven Question Answering datasetcited by 189
- 2023Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verificationcited by 166
- 2023MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoningcited by 155
- 2023RestGPT: Connecting Large Language Models with Real-World RESTful APIscited by 129
- 2023CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsetscited by 122
- 2023GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Informationcited by 115
- 2023SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Researchcited by 112
- 2024TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Taskscited by 70
- 2023Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculumcited by 64
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Citing papers per year: 2024: 13; 2025: 28; 2026: 28.
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