Search Results for author:
Found 13 papers, 6 papers with code
Biology Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models
Large language models have already demonstrated their formidable capabilities in general domains, ushering in a revolutionary transformation.
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
Previous endeavours often treat the molecule as a general SMILES string or molecular graph, neglecting the fine-grained alignments between the molecular sub-structures and the descriptive textual phrases, which are crucial for accurate and explainable predictions.
MolReFlect: Towards Fine-grained In-Context Alignment between Molecules and Texts
Previous endeavours often treat the molecule as a general SMILES string or molecular graph, neglecting the fine-grained alignments between the molecular sub-structures and the descriptive textual phrases, which are crucial for accurate and explainable predictions.
Ranked #1 on
Molecule Captioning
on ChEBI-20
CrystalX: Ultra-Precision Crystal Structure Resolution and Error Correction Using Deep Learning
Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences.
MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses
In this work, we investigate this central research question: Can LLMs automatically discover novel and valid chemistry research hypotheses given only a chemistry research background (consisting of a research question and/or a background survey), without limitation on the domain of the research question?
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
This paper presents an advanced mathematical problem-solving framework, LLaMA-Berry, for enhancing the mathematical reasoning ability of Large Language Models (LLMs).
ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area
We benchmark ChemVLM against a range of open-source and proprietary multimodal large language models on various tasks.
Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
This paper introduces the MCT Self-Refine (MCTSr) algorithm, an innovative integration of Large Language Models (LLMs) with Monte Carlo Tree Search (MCTS), designed to enhance performance in complex mathematical reasoning tasks.
Physical formula enhanced multi-task learning for pharmacokinetics prediction
Overall, our work illustrates the benefits and potential of using PEMAL in AIDD and other scenarios with data scarcity and noise.
Large Language Models are In-Context Molecule Learners
Specifically, ICMA incorporates the following three stages: Hybrid Context Retrieval, Post-retrieval Re-ranking, and In-context Molecule Tuning.
ChemLLM: A Chemical Large Language Model
However, the community lacks an LLM specifically designed for chemistry.
An Comparative Analysis of Different Pitch and Metrical Grid Encoding Methods in the Task of Sequential Music Generation
Results display a general phenomenon of over-fitting from two aspects, the pitch embedding space and the test loss of the single-token grid encoding.
Minimax Weight Learning for Absorbing MDPs
Reinforcement learning policy evaluation problems are often modeled as finite or discounted/averaged infinite-horizon MDPs.
