Search Results for author:
Found 9 papers, 4 papers with code
Knowledge Graph Enhanced Language Agents for Recommendation
Our key insight is that the paths in a KG can capture complex relationships between users and items, eliciting the underlying reasons for user preferences and enriching user profiles.
ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
We hope our benchmark and model can facilitate and promote more research on chemical QA.
Data Interpreter: An LLM Agent For Data Science
On InfiAgent-DABench, it achieves a 25% performance boost, raising accuracy from 75. 9% to 94. 9%.
Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark
Our findings confirm that FM offers a more logical approach to evaluating scientific summaries.
SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark
The paper introduces SceMQA, a novel benchmark for scientific multimodal question answering at the college entrance level.
Large Language Model based Multi-Agents: A Survey of Progress and Challenges
To provide the community with an overview of this dynamic field, we present this survey to offer an in-depth discussion on the essential aspects of multi-agent systems based on LLMs, as well as the challenges.
Beyond the Typical: Modeling Rare Plausible Patterns in Chemical Reactions by Leveraging Sequential Mixture-of-Experts
Reaction prediction, a critical task in synthetic chemistry, is to predict the outcome of a reaction based on given reactants.
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks
In this paper, rather than pursuing state-of-the-art performance, we aim to evaluate capabilities of LLMs in a wide range of tasks across the chemistry domain.
Few-shot News Recommendation via Cross-lingual Transfer
Second, the user preference over these topics is transferable across different platforms.
