Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation | Paper Citation Record

Observation f7540bac-d383-4e73-8244-d11db3c25e66 · outbound

This paper cites Crystal diffusion variational autoencoder for periodic material generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Crystal diffusion variational autoencoder for periodic material generation,

Reference 1

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Observation 78e11b98-7170-4db8-8153-bcf9dd413d2b · outbound

This paper cites GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation

Reference 2

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Observation ee50e27e-e4ee-40ed-b2af-0ec0d23bcea9 · outbound

This paper cites Accelerating 3d molecule generation via jointly geometric optimal transport,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Accelerating 3d molecule generation via jointly geometric optimal transport,

Reference 3

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This paper cites Diffusion-driven domain adaptation for generating 3d molecules,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Diffusion-driven domain adaptation for generating 3d molecules,

Reference 4

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This paper cites Crystalline material discovery in the era of artificial intelligence,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Crystalline material discovery in the era of artificial intelligence,

Reference 5

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This paper cites Estimation of the size of drug-like chemical space based on gdb-17 data,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Estimation of the size of drug-like chemical space based on gdb-17 data,

Reference 6

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This paper cites Impact of high-throughput screening in biomedical research,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Impact of high-throughput screening in biomedical research,

Reference 7

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Observation 70c503db-c76e-4271-98c3-c821b78516b4 · outbound

This paper cites Strategy to discover diverse optimal molecules in the small molecule universe,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Strategy to discover diverse optimal molecules in the small molecule universe,

Reference 8

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This paper cites Medgan: optimized generative adversarial network with graph convolutional networks for novel molecule design,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Medgan: optimized generative adversarial network with graph convolutional networks for novel molecule design,

Reference 9

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This paper cites Equivariant flow matching with hybrid probability transport for 3d molecule generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Equivariant flow matching with hybrid probability transport for 3d molecule generation,

Reference 10

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Observation 724db459-2906-4db3-9e93-c0b6a55b16f9 · outbound

This paper cites Auto-encoding variational bayes,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Auto-encoding variational bayes,

Reference 11

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Observation 97862e60-44e2-4b74-beaa-09c79bb8acab · outbound

This paper cites Automatic chemical design using a data-driven continuous representation of molecules,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Automatic chemical design using a data-driven continuous representation of molecules,

Reference 12

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Observation a263c8a1-1f89-4d36-877f-a6e875e1e1da · outbound

This paper cites Junction tree variational autoen- coder for molecular graph generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Junction tree variational autoen- coder for molecular graph generation,

Reference 13

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This paper cites Limo: 10 Latent inceptionism for targeted molecule generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Limo: 10 Latent inceptionism for targeted molecule generation,

Reference 14

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Observation f5f4fcc1-d558-4792-a116-f3f132cdc1af · outbound

This paper cites Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

Reference 15

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This paper cites drugan: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation drugan: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico,

Reference 16

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This paper cites Graph convolutional policy network for goal-directed molecular graph generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Graph convolutional policy network for goal-directed molecular graph generation,

Reference 17

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This paper cites Graphdf: A discrete flow model for molecular graph generation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Graphdf: A discrete flow model for molecular graph generation,

Reference 18

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This paper cites GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Reference 19

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Observation d2d4828d-8ef3-4db2-8481-fff802d9da52 · outbound

This paper cites Constrained graph variational autoencoders for molecule design,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Constrained graph variational autoencoders for molecule design,

Reference 20

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This paper cites Retrieval-based Controllable Molecule Generation.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Retrieval-based Controllable Molecule Generation

Reference 21

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This paper cites Qwen Technical Report.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Qwen Technical Report

Reference 22

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This paper cites Language models can learn complex molecular distributions,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Language models can learn complex molecular distributions,

Reference 23

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This paper cites Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules,

Reference 24

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This paper cites A systematic study of key elements underlying molecular property prediction,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation A systematic study of key elements underlying molecular property prediction,

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This paper cites A review of molecular representation in the age of machine learning,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation A review of molecular representation in the age of machine learning,

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This paper cites Chemformer: a pre- trained transformer for computational chemistry,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Chemformer: a pre- trained transformer for computational chemistry,

Reference 27

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This paper cites Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective,

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This paper cites Conversational drug editing using retrieval and domain feedback,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Conversational drug editing using retrieval and domain feedback,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Domain- agnostic molecular generation with chemical feedback,

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This paper cites MolecularRNN: Generating realistic molecular graphs with optimized properties.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation MolecularRNN: Generating realistic molecular graphs with optimized properties

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This paper cites MARS: Markov Molecular Sampling for Multi-objective Drug Discovery.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation MARS: Markov Molecular Sampling for Multi-objective Drug Discovery

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This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Tulu 3: Pushing Frontiers in Open Language Model Post-Training

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This paper cites Training language models to follow instructions with human feedback,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Training language models to follow instructions with human feedback,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation LoRA: Low-Rank Adaptation of Large Language Models

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling,

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This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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This paper cites Learning Multimodal Graph-to-Graph Translation for Molecular Optimization.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Learning Multimodal Graph-to-Graph Translation for Molecular Optimization

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This paper cites Deep learn- ing for molecular design—a review of the state of the art,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Deep learn- ing for molecular design—a review of the state of the art,

Reference 39

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Autoencoders, unsupervised learning, and deep architectures,

Reference 40

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This paper cites Efficient multi-objective molecular optimization in a continuous latent space,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Efficient multi-objective molecular optimization in a continuous latent space,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Generative adversarial networks,

Reference 42

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Reinforced ad- versarial neural computer for de novo molecular design,

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This paper cites De novo generation of hit-like molecules from gene expression signa- tures using artificial intelligence,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation De novo generation of hit-like molecules from gene expression signa- tures using artificial intelligence,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Hierarchical generation of molecular graphs using structural motifs,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Genetic algorithms are strong baselines for molecule generation

Reference 46

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space

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This paper cites Regression transformer enables concurrent sequence regression and generation for molecular language modelling,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Regression transformer enables concurrent sequence regression and generation for molecular language modelling,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Translation between Molecules and Natural Language

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This paper cites Hierarchical deep re- inforcement learning for multi-robot cooperation in partially observable environment,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Hierarchical deep re- inforcement learning for multi-robot cooperation in partially observable environment,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collab- oration 0,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Scaling laws for reward model overoptimization,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Deep reinforcement learning for de novo drug design,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Proximal Policy Optimization Algorithms

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This paper cites Reinforcement learning with verifiable rewards: Grpo’s effective loss, dynamics, and success amplification,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Reinforcement learning with verifiable rewards: Grpo’s effective loss, dynamics, and success amplification,

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This paper cites Self- referencing embedded strings (selfies): A 100% robust molecular string representation,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Self- referencing embedded strings (selfies): A 100% robust molecular string representation,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Zinc 15–ligand discovery for everyone,

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This paper cites Quantifying the chemical beauty of drugs,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Quantifying the chemical beauty of drugs,

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Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Optimization of molecules via deep reinforcement learning,

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This paper cites Extended-connectivity fingerprints,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Extended-connectivity fingerprints,

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This paper cites Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Reference 62

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Observation 70dd1fe4-a02b-4b26-a492-9ec369a7b6b3 · outbound

This paper cites Training chain- of-thought via latent-variable inference,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Training chain- of-thought via latent-variable inference,

Reference 63

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Observation ae5926b7-33cb-4f8d-93b0-fb5d51422def · outbound

This paper cites RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning

Reference 64

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Observation 2129baba-e7a5-445f-b1e2-aa2714dc6e00 · outbound

This paper cites Moleculenet: a benchmark for molecular machine learning,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Moleculenet: a benchmark for molecular machine learning,

Reference 65

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Observation 8c6a9ff5-b478-43a1-bd1c-422e12c68a34 · outbound

This paper cites Qwen3 Technical Report.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Qwen3 Technical Report

Reference 66

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Observation fc250746-a332-4b35-9bdf-ebbdc75566a7 · outbound

This paper cites Transformers: State- of-the-art natural language processing,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Transformers: State- of-the-art natural language processing,

Reference 67

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Observation 11116f65-dbcc-4a81-8352-71f3a0a7d98f · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Pytorch: An imperative style, high-performance deep learning library,

Reference 68

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Observation 3e3ed461-39ba-4d15-adb8-da95984cca7b · outbound

This paper cites Virtual compound libraries in computer-assisted drug discovery,.

Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation Virtual compound libraries in computer-assisted drug discovery,

Reference 69

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