EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization | Paper Citation Record

Observation 01b08e68-be38-4bd5-b993-40d03c50e057 · outbound

This paper cites A new age in protein design empowered by deep learning,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization A new age in protein design empowered by deep learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.286241Z

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Observation 3b11b215-9941-4ba4-95eb-063408a8ed62 · outbound

This paper cites Sparks of function by de novo protein design,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Sparks of function by de novo protein design,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.269217Z

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Observation 69eb93dc-3bd1-4d67-abc8-da09080586be · outbound

This paper cites Highly accurate protein structure prediction with alphafold,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Highly accurate protein structure prediction with alphafold,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.252222Z

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Observation 711014f9-b882-4ff4-a6da-be3b9529ce12 · outbound

This paper cites Representing long-range context for graph neural networks with global attention,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Representing long-range context for graph neural networks with global attention,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.234702Z

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Observation 2f4ed58f-dd93-4469-931b-e24cb44cab43 · outbound

This paper cites Robust deep learning–based protein sequence design using proteinmpnn,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Robust deep learning–based protein sequence design using proteinmpnn,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.217475Z

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Observation 372e20ed-ec65-4625-a9ba-5754200c73b0 · outbound

This paper cites PiFold: Toward effective and efficient protein inverse folding.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization PiFold: Toward effective and efficient protein inverse folding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.033673Z

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Observation ab0e7c70-8db2-4b7f-978e-7da1f908948a · outbound

This paper cites The graph neural network model,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization The graph neural network model,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.039850Z

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Observation 7d6e4ba3-1e4d-4334-a0b8-09ea77361fca · outbound

This paper cites Structure-informed language models are protein designers,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Structure-informed language models are protein designers,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.192499Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8906621d-d29c-4577-ae2e-8026c96e8e19 · outbound

This paper cites Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.049695Z

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Observation 8ef7157b-41ee-4c73-aef5-7b86faa76d90 · outbound

This paper cites Graph denoising diffusion for inverse protein folding,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Graph denoising diffusion for inverse protein folding,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.176645Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1983ea13-d6c6-4018-aa4c-f2a665e5d7ee · outbound

This paper cites Bridge-IF: Learning Inverse Protein Folding with Markov Bridges.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Bridge-IF: Learning Inverse Protein Folding with Markov Bridges

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:52:27.595335Z

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Observation 7b1deb16-4c84-46ee-b2d0-8473ee4a8e3c · outbound

This paper cites Diffusion Model with Representation Alignment for Protein Inverse Folding.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Diffusion Model with Representation Alignment for Protein Inverse Folding

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.066175Z

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Observation 55704c6b-fbbc-406a-a9bf-529a926e11af · outbound

This paper cites Cath–a hierarchic classification of protein domain structures,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Cath–a hierarchic classification of protein domain structures,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.159855Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22e81ff2-75c5-4c59-9e2d-fec369a2a3ac · outbound

This paper cites Protein sequence design by conformational landscape optimization,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Protein sequence design by conformational landscape optimization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.143209Z

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Observation 75d8902f-7cc3-4d58-91ea-2abd421b9b1d · outbound

This paper cites RetroBridge: Modeling Retrosynthesis with Markov Bridges.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization RetroBridge: Modeling Retrosynthesis with Markov Bridges

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.082337Z

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Observation 0ba13296-7917-43ee-a6d5-70ad4416c92a · outbound

This paper cites Disco: Diffusion schrödinger bridge for molecular conformer optimization,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Disco: Diffusion schrödinger bridge for molecular conformer optimization,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.127097Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fe16befd-9a33-4ca1-a1b4-6a274fa06c99 · outbound

This paper cites Direct preference opti- mization: Your language model is secretly a reward model,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Direct preference opti- mization: Your language model is secretly a reward model,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.109687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7008be01-0854-453c-82c0-f3e4f9eb3b31 · outbound

This paper cites Generative models for graph-based protein design,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Generative models for graph-based protein design,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.093635Z

Source-reported events for the cited work

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Observation bb6bd383-241b-46ef-a17e-7c5d8342e35b · outbound

This paper cites AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.106096Z

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Observation 34bec870-a1ba-48a9-b795-11c3bf2662a8 · outbound

This paper cites Generative De Novo Protein Design with Global Context.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Generative De Novo Protein Design with Global Context

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:52:27.512862Z

Source-reported events for the cited work

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Observation cb0fb4f5-8606-4436-a782-9cfc433a684c · outbound

This paper cites Structgnn: an efficient graph neural network framework for static structural analysis,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Structgnn: an efficient graph neural network framework for static structural analysis,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.076226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 14a0a204-b880-4cf3-99cc-248d556d8bc0 · outbound

This paper cites Learning inverse folding from millions of predicted structures,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Learning inverse folding from millions of predicted structures,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.059712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9899f40b-539b-4db8-840c-a68d706d8a14 · outbound

This paper cites Illuminating protein space with a programmable generative model,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Illuminating protein space with a programmable generative model,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.039661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 48338a00-e6c4-4e1e-a14d-360c8cd4d98e · outbound

This paper cites Accurate and robust protein sequence design with carbondesign,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Accurate and robust protein sequence design with carbondesign,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.020661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 440709f8-46a6-4f2d-950a-5a2cc4e2c5c0 · outbound

This paper cites Structured denoising diffusion models in discrete state-spaces,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Structured denoising diffusion models in discrete state-spaces,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:28.002499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 89ff6185-529f-4299-922b-7ec88307cd54 · outbound

This paper cites Protein design using physics informed neural networks,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Protein design using physics informed neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.985253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d4b4f6cd-378d-487d-8d7d-6331790d28f8 · outbound

This paper cites Machine learning for evolutionary- based and physics-inspired protein design: Current and future synergies,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Machine learning for evolutionary- based and physics-inspired protein design: Current and future synergies,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.967492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 159c8552-792c-424c-acd4-e480be367974 · outbound

This paper cites Protein structure prediction using rosetta,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Protein structure prediction using rosetta,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.950587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation def2e76f-2a50-419e-9042-f32f402f2f9b · outbound

This paper cites Deep reinforcement learning from human preferences,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Deep reinforcement learning from human preferences,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.164730Z

Source-reported events for the cited work

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Observation 74a12679-4088-417b-a4e7-9ea272ff9adf · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Fine-Tuning Language Models from Human Preferences

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.171463Z

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Observation 40f023bd-aaa9-4631-8d0a-3169fe0b869d · outbound

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

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Training language models to follow instructions with human feedback,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.178917Z

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Observation 5ecd9988-03e4-4cc7-bb79-938b95e05943 · outbound

This paper cites Safe RLHF: Safe Reinforcement Learning from Human Feedback.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Safe RLHF: Safe Reinforcement Learning from Human Feedback

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.187623Z

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Observation 06c47b10-2a54-4385-ad6f-d795a69f70ba · outbound

This paper cites Rlaif: Scaling reinforcement learning from human feedback with ai feedback,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Rlaif: Scaling reinforcement learning from human feedback with ai feedback,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.193814Z

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Observation 78e3f370-cbac-4a98-995a-4441e14109d8 · outbound

This paper cites Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.903001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e96c7da8-9d79-4d75-b9ca-f0ff310b82ac · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Training Diffusion Models with Reinforcement Learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.206534Z

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Observation 733a98db-9006-464c-a516-ffcaa6a4d2b8 · outbound

This paper cites Diffusion model alignment using direct preference optimization,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Diffusion model alignment using direct preference optimization,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.886138Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9dfb36e7-7581-4d4b-9c7d-d3cf494fa107 · outbound

This paper cites Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.870738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 33836300-b0b3-4970-a835-777e6f47addf · outbound

This paper cites Scalable diffusion models with transformers,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Scalable diffusion models with transformers,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.221812Z

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Observation dd1a78e6-2d6b-4808-b6a6-83f752340c36 · outbound

This paper cites Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.226979Z

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Observation 06daa3c9-084e-4969-8e93-6518880ab798 · outbound

This paper cites Bindinggym: A large-scale mutational dataset toward deciphering protein-protein interactions,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Bindinggym: A large-scale mutational dataset toward deciphering protein-protein interactions,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.839231Z

Source-reported events for the cited work

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Observation 5a32ad02-f3ac-4ea1-874b-35649799502d · outbound

This paper cites Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.821751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d0f23f63-ca57-40d2-a843-28409963429c · outbound

This paper cites Rotamer density estimator is an unsupervised learner of the effect of mutations on protein-protein interaction,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Rotamer density estimator is an unsupervised learner of the effect of mutations on protein-protein interaction,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.803569Z

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Observation 5cedac6d-5bc1-4bc0-8642-9f134ff997a3 · outbound

This paper cites Surface-vqmae: Vector-quantized masked auto-encoders on molecular surfaces,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Surface-vqmae: Vector-quantized masked auto-encoders on molecular surfaces,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.786464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 45e1e1f5-6f16-4c7e-b14c-9ff7f6b22656 · outbound

This paper cites Improved denoising diffusion probabilistic models,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Improved denoising diffusion probabilistic models,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.770183Z

Source-reported events for the cited work

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Observation 41a642ad-beb9-4fb5-9bad-ee47340e1173 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Adam: A Method for Stochastic Optimization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.260565Z

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Observation b2095bc2-2895-4df7-8116-f7cb612b1701 · outbound

This paper cites Attention is all you need,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Attention is all you need,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.265372Z

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Observation d0d9d678-23ed-433a-89ef-768aa8ff3b7b · outbound

This paper cites Learning from Protein Structure with Geometric Vector Perceptrons.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Learning from Protein Structure with Geometric Vector Perceptrons

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.270401Z

Source-reported events for the cited work

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Observation 4266702c-cec8-4511-9c86-ed6abc719923 · outbound

This paper cites Global-context aware generative protein design,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Global-context aware generative protein design,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.741480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 16c291fa-6790-4558-a277-7df93ad81cde · outbound

This paper cites Deep learning guided optimization of human antibody against sars-cov-2 variants with broad neutralization,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Deep learning guided optimization of human antibody against sars-cov-2 variants with broad neutralization,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.722113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2797d1a5-5b4e-4871-b447-9f9bedcdd9e0 · outbound

This paper cites The hdock server for integrated protein–protein docking,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization The hdock server for integrated protein–protein docking,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.702979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2458cc04-927a-486f-a74a-fb32a9e7b4a5 · outbound

This paper cites Language models of protein sequences at the scale of evolution enable accurate structure prediction,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Language models of protein sequences at the scale of evolution enable accurate structure prediction,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.685217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e87d97c-e859-47f7-8739-4960b690f5c1 · outbound

This paper cites Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.296672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 510ec5d7-7f2c-4a96-b277-1396b24cf02a · outbound

This paper cites Multi-level Interaction Modeling for Protein Mutational Effect Prediction.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Multi-level Interaction Modeling for Protein Mutational Effect Prediction

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:27.301516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 351337d0-fadf-4790-8240-5be09d10fe76 · outbound

This paper cites Foldx 5.0: working with rna, small molecules and a new graphical interface,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization Foldx 5.0: working with rna, small molecules and a new graphical interface,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.668996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 57d386b1-c3b8-441a-8594-2bc7ebcb3b2e · outbound

This paper cites The rosetta all-atom energy function for macromolecular modeling and design,.

EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization The rosetta all-atom energy function for macromolecular modeling and design,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:52:27.651920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Outbound references

Pith citing papers