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Paper Citation Record · LEDGER

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions

As of 20 August 2026, this Paper Citation Record lists 100 of 189 outbound references and 0 inbound Pith citation observations for arXiv:2506.05766.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.05766 v1

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measured 100 of 189 reference resolution

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100 of 189 outbound references displayed

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Outbound references

Observation edf53a7c-b77f-41af-8d7f-dcf73db01721 · outbound

This paper cites Text-based question answering from information retrieval and deep neural network perspectives: A survey.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Text-based question answering from information retrieval and deep neural network perspectives: A survey

Reference 1

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Observation 65dfdbfb-3c44-4dd3-858d-5a67c07f81ab · outbound

This paper cites Synthetic dialogue dataset generation using LLM agents.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Synthetic dialogue dataset generation using LLM agents

Reference 2

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Observation dc872ce5-6551-497e-8d92-014e2e7d0332 · outbound

This paper cites Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation

Reference 3

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This paper cites GPT-4 Technical Report.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions GPT-4 Technical Report

Reference 4

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This paper cites Together AI – The AI Acceleration Cloud - Fast Inference, Fine-Tuning & Training — together.ai.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Together AI – The AI Acceleration Cloud - Fast Inference, Fine-Tuning & Training — together.ai

Reference 5

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This paper cites FLAIR: An easy-to-use framework for state-of-the-art NLP.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions FLAIR: An easy-to-use framework for state-of-the-art NLP

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Observation ec77c365-582f-4890-997e-f21a7518dccc · outbound

This paper cites Multimodal large language models in health care: appli- cations, challenges, and future outlook.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Multimodal large language models in health care: appli- cations, challenges, and future outlook

Reference 7

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This paper cites Claude 3.7 system card - Anthropic — docs.anthropic.com, 2025.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Claude 3.7 system card - Anthropic — docs.anthropic.com, 2025

Reference 8

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This paper cites Self-rag: Learning to retrieve, generate, and critique through self-reflection.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Self-rag: Learning to retrieve, generate, and critique through self-reflection

Reference 9

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This paper cites The human proteome in druggable - The Human Protein Atlas — proteinatlas.org.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions The human proteome in druggable - The Human Protein Atlas — proteinatlas.org

Reference 10

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 11

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This paper cites Interactive question answering systems: Literature review.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Interactive question answering systems: Literature review

Reference 12

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 14

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This paper cites Dated data: Tracing knowledge cutoffs in large language models.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Dated data: Tracing knowledge cutoffs in large language models

Reference 15

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This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 17

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This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A survey on rag meeting llms: Towards retrieval-augmented large language models

Reference 18

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems

Reference 19

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 20

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This paper cites Introducing Gemini 2.0: our new AI model for the agentic era — blog.google.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Introducing Gemini 2.0: our new AI model for the agentic era — blog.google

Reference 21

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A Survey on LLM-as-a-Judge

Reference 22

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This paper cites On the effectiveness of large language models in domain-specific code generation.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions On the effectiveness of large language models in domain-specific code generation

Reference 23

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Domain-specific language model pretraining for biomedical natural language processing

Reference 24

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Towards Generalist Prompting for Large Language Models by Mental Models

Reference 25

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions The fog index after twenty years

Reference 26

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 27

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This paper cites What can large language models do in chemistry? a comprehensive benchmark on eight tasks.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions What can large language models do in chemistry? a comprehensive benchmark on eight tasks

Reference 28

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Polypharmacy: evaluating risks and deprescribing

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Inductive representation learning on large graphs

Reference 30

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Promqa: Question answering dataset for multimodal procedural activity understanding

Reference 31

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions The ability of chatgpt in paraphrasing texts and reducing plagiarism: a descriptive analysis

Reference 32

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This paper cites Prompt engineering of gpt-4 for chemical research: what can/cannot be done? Science and Technology of Advanced Materials: Methods, 3(1):2260300, 2023.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Prompt engineering of gpt-4 for chemical research: what can/cannot be done? Science and Technology of Advanced Materials: Methods, 3(1):2260300, 2023

Reference 33

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions G-retriever: Retrieval-augmented generation for textual graph understanding and question answering

Reference 34

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Consistency training by synthetic question generation for conversational question answering

Reference 35

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature Alignment

Reference 36

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BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions GRAG: Graph Retrieval-Augmented Generation

Reference 37

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Observation 7b5bfeae-11e2-4ce9-9a1f-a75af2e8a386 · outbound

This paper cites Om- nimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Om- nimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm

Reference 38

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Observation 99454f12-6c2a-4371-8472-ba4db1313b76 · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

Reference 39

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Observation 5dede6a9-20ea-4857-90f6-8d1e65d0d1d9 · outbound

This paper cites GPT-4o System Card.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions GPT-4o System Card

Reference 40

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Observation 947d9b2a-5077-4f79-9106-ed8100932a40 · outbound

This paper cites Atlas: few-shot learning with retrieval augmented language models.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Atlas: few-shot learning with retrieval augmented language models

Reference 41

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source=pdf_text observed=2026-08-07T10:19:14.681861Z digest=sha256:cb5d6b6e68264dbb9de9facd2f4e52e495566636bfc51e4b64a3f64f0e341b1b

Observation 2079f778-f72d-4b35-8ce4-579143af336f · outbound

This paper cites A survey on knowledge graphs: Representation, acquisition, and applications.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A survey on knowledge graphs: Representation, acquisition, and applications

Reference 42

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Observation e1fb1208-c5e9-41fb-b0fc-0e471457e3bb · outbound

This paper cites Mistral 7B.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Mistral 7B

Reference 43

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source=pdf_text observed=2026-08-07T10:19:14.951207Z digest=sha256:4c09d8df9ccc70de867e3f1894c5de81b163e75148fa7b6e8b94a0da5a880118

Observation 88ad2eff-ea4f-4fa3-be4c-2f5fdf7a8d3a · outbound

This paper cites Active retrieval augmented generation.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Active retrieval augmented generation

Reference 44

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source=pdf_text observed=2026-08-07T10:19:15.157767Z digest=sha256:94222a1f8bcc29502d08db820bdad5f1e82323b1a6d81c4d8f5c6a0f8925a2ed

Observation 239fac3b-4f6e-4e57-9440-00a3b6622c60 · outbound

This paper cites FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research

Reference 45

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Observation 92430c4d-fd2b-4bfe-a143-f09fd0947f58 · outbound

This paper cites PubMedQA: A dataset for biomedical research question answering.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions PubMedQA: A dataset for biomedical research question answering

Reference 46

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source=pdf_text observed=2026-08-07T10:19:15.464461Z digest=sha256:63364b4518263e0511f32bb421b00a08202019f1275ab244c08837e8f31c6718

Observation bb7ba82c-0117-43e4-910a-4192e9240593 · outbound

This paper cites Biomedical question answering: A survey of approaches and challenges.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Biomedical question answering: A survey of approaches and challenges

Reference 47

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Observation 535522b1-80dc-4950-94dc-d891dd851fbe · outbound

This paper cites Medcpt: Contrastive pre-trained transformers with large-scale pubmed search logs for zero-shot biomedical information retrieval.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Medcpt: Contrastive pre-trained transformers with large-scale pubmed search logs for zero-shot biomedical information retrieval

Reference 48

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source=pdf_text observed=2026-08-07T10:19:16.026205Z digest=sha256:60090d527ebbb5716f2e41d1fd17e37d6102ed47276a1659447e3cf0766a339d

Observation 2a1c8135-0014-4c59-8860-c11e93975752 · outbound

This paper cites Wikimedia data for AI: a review of wikimedia datasets for NLP tasks and AI-assisted editing.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Wikimedia data for AI: a review of wikimedia datasets for NLP tasks and AI-assisted editing

Reference 49

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source=pdf_text observed=2026-08-07T10:19:16.160907Z digest=sha256:910d3458413e38d61823234dc1cccba3be3d408a45fb817f20303bde03cfb1f6

Observation f5858bd2-6c0a-49b9-94dd-2833286dc45d · outbound

This paper cites SemEval-2024 task 2: Safe biomedical natural language inference for clinical trials.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions SemEval-2024 task 2: Safe biomedical natural language inference for clinical trials

Reference 50

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source=pdf_text observed=2026-08-07T10:19:16.317322Z digest=sha256:8c34acbddf523687f3da44ff34c05644f67d3fc5f883bf0f21e0cbb2a849379a

Observation b12bee28-bed5-4940-a07c-014d85156c5d · outbound

This paper cites an unresolved cited work.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 51

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Observation f714648e-057f-4632-85e9-153ab47a6e2f · outbound

This paper cites Dense passage retrieval for open-domain question answering.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Dense passage retrieval for open-domain question answering

Reference 52

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source=pdf_text observed=2026-08-07T10:19:16.689466Z digest=sha256:e73b741721a4773e199b7133d4e9a9b7456426e0d4906d692144d463ea58f10b

Observation df2cb6ae-4cf5-4b42-be06-11f6e3cf5421 · outbound

This paper cites Pubchem 2025 update.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Pubchem 2025 update

Reference 53

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source=pdf_text observed=2026-08-07T10:19:16.849080Z digest=sha256:b0461aaa9c14e29b8c19b27db99bf6e8c680fe436938a1aa50ac7e027adc6888

Observation 1e86cbff-c0f5-4a23-b83e-45a45a5e9a96 · outbound

This paper cites Benchmarking cognitive biases in large language models as evaluators.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Benchmarking cognitive biases in large language models as evaluators

Reference 54

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Observation fcbc2d49-f82b-4cb3-82f4-a6be15fe7e9f · outbound

This paper cites From Data to Commonsense Reasoning: The Use of Large Language Models for Explainable AI.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions From Data to Commonsense Reasoning: The Use of Large Language Models for Explainable AI

Reference 55

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local_arxiv, observed 2026-08-07T10:19:33.165383Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f5d2a5b4-d12c-47fe-a996-4d1a4d565012 · outbound

This paper cites Stitch: interaction networks of chemicals and proteins.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Stitch: interaction networks of chemicals and proteins

Reference 56

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source=pdf_text observed=2026-08-07T10:19:17.458128Z digest=sha256:be0acc1150e74ec34f526704f813ae63941545627f70d00ad1dea3233a732f37

Observation 93d99132-2131-4035-b2ae-eaac6f7d2318 · outbound

This paper cites SNAP Datasets: Stanford large network dataset collection.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions SNAP Datasets: Stanford large network dataset collection

Reference 57

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Observation 272fde41-2e49-455a-86fb-0469f576c830 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Retrieval- augmented generation for knowledge-intensive nlp tasks

Reference 58

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source=pdf_text observed=2026-08-07T10:19:17.814950Z digest=sha256:3dc34e642cf9cd7ab8f4182f708fdb6d6bc8ec12ce6d1c77ffc1729647e62d9b

Observation 5597e1fd-6fb8-4390-af57-2badcdabdb1c · outbound

This paper cites From generation to judgment: Opportunities and challenges of llm-as-a-judge.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions From generation to judgment: Opportunities and challenges of llm-as-a-judge

Reference 59

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source=pdf_text observed=2026-08-07T10:19:17.958056Z digest=sha256:8e57d87bae09e93c703b2b52b554cf143ae5bd69ffc3c781aa2919ca91b3bd49

Observation ed532e55-2fb7-49cb-9a82-e3aa137e067c · outbound

This paper cites LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

Reference 60

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source=pdf_text observed=2026-08-07T10:19:18.127869Z digest=sha256:3c6a7cff5a23e2cc677d8238e2002318147562ba14a52512ba1cd2dffcc3a415

Observation 95304716-6757-4b67-8ef5-1b911181afb9 · outbound

This paper cites Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking

Reference 61

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Observation 018baf74-84a1-4821-96a0-0cc05f8f814d · outbound

This paper cites Bigsmiles: a structurally-based line notation for describing macromolecules.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Bigsmiles: a structurally-based line notation for describing macromolecules

Reference 62

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Observation 58bbd493-92b4-488b-857a-bec5488eb78c · outbound

This paper cites Synthetic Context Generation for Question Generation.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Synthetic Context Generation for Question Generation

Reference 63

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local_arxiv, observed 2026-08-07T10:19:32.921739Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:19:18.379936Z digest=sha256:5a5c26a6ac116e7ccfcf01fe0f8942cf380c1e5ebb1b705876ce338c715c2ff4

Observation 1a97ff49-a58d-457b-88c6-60d8b00b176c · outbound

This paper cites Lost in the middle: How language models use long contexts.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Lost in the middle: How language models use long contexts

Reference 64

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Observation e69f5891-fc57-4782-b41e-35aa36d96a7c · outbound

This paper cites Chatqa: Surpassing gpt-4 on conversational qa and rag.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Chatqa: Surpassing gpt-4 on conversational qa and rag

Reference 65

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source=pdf_text observed=2026-08-07T10:19:18.486122Z digest=sha256:1f0764eae9f2bd7ffd0ee9976bafb796f916c1f7b1bda95b04e59dfeac538720

Observation 3e4f465a-8f19-4f6c-a9bc-73b486225dd8 · outbound

This paper cites Biochemistry, essential amino acids.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Biochemistry, essential amino acids

Reference 66

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Observation da3fd446-9fa2-4525-a405-577d9d0f03fd · outbound

This paper cites Decoupled weight decay regularization.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Decoupled weight decay regularization

Reference 67

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source=pdf_text observed=2026-08-07T10:19:18.613465Z digest=sha256:e225037f88eb69f5f711d49e15b1a7a92b46fb76ae29a22fbdd6b04015ed193a

Observation 8edebcc0-201c-40e6-9b34-6a4445fd1dd1 · outbound

This paper cites an unresolved cited work.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 68

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source=pdf_text observed=2026-08-07T10:19:18.675669Z digest=sha256:9582bed4907882ef3e2072a050751571ff142b49d8b51d938a6a6ca9ec87e3b5

Observation f6536d96-2dcf-40f9-aaf7-67299d8f7880 · outbound

This paper cites ReACC: A retrieval-augmented code completion framework.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions ReACC: A retrieval-augmented code completion framework

Reference 69

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no resolver link, observed 2026-08-07T10:19:18.745228Z

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source=pdf_text observed=2026-08-07T10:19:18.745228Z digest=sha256:ace73482e5465e9e4ef8a1b9dac4dde77ac2922cd18e930b7a8e4e5eb9ed6f1a

Observation 619f42b0-0c76-4fa0-a77b-222ec0b5d183 · outbound

This paper cites MoleculeQA: A dataset to evaluate factual accuracy in molecular comprehension.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions MoleculeQA: A dataset to evaluate factual accuracy in molecular comprehension

Reference 70

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source=pdf_text observed=2026-08-07T10:19:18.802578Z digest=sha256:d66b4aa05d4d28276feff3aa29eee11a211e134b3603dc2d260b499a5e4b2d96

Observation ab8ab720-a08a-4933-958e-2221424f109b · outbound

This paper cites A study on the efficiency and gen- eralization of light hybrid retrievers.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A study on the efficiency and gen- eralization of light hybrid retrievers

Reference 71

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Observation 5c3851ab-92af-42a3-9262-34c7b65c1aad · outbound

This paper cites Biomedgpt: An open multimodal large language model for biomedicine.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Biomedgpt: An open multimodal large language model for biomedicine

Reference 72

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no resolver link, observed 2026-08-07T10:19:19.011625Z

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source=pdf_text observed=2026-08-07T10:19:19.011625Z digest=sha256:fd4badbfa41c94f974fbd69789d9f992a76d14c04b0e515ae9286ed5c1282ed5

Observation f987a269-1830-4e88-962b-63cfa445b09e · outbound

This paper cites Realrag: Retrieval-augmented realistic image generation via self-reflective contrastive learning.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Realrag: Retrieval-augmented realistic image generation via self-reflective contrastive learning

Reference 73

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Observation 19fca9bf-3aae-405f-8d73-7030bee00d08 · outbound

This paper cites Smith Marsh.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Smith Marsh

Reference 74

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Observation 3013764f-7bb5-4960-80f3-842558550698 · outbound

This paper cites doi: 10.18653/v1/2023.acl-short.139.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions doi: 10.18653/v1/2023.acl-short.139

Reference 75

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Observation 05412d9f-646f-473d-9a5c-ebf9022e508a · outbound

This paper cites GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

Reference 76

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Observation 93663203-679f-4c4a-8523-67eca9437942 · outbound

This paper cites A Survey of Multimodal Retrieval-Augmented Generation.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions A Survey of Multimodal Retrieval-Augmented Generation

Reference 77

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Observation 59ee0a18-241e-48a5-833b-511cda702dd9 · outbound

This paper cites Laypeople’s use of and attitudes toward large language models and search engines for health queries: Survey study.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Laypeople’s use of and attitudes toward large language models and search engines for health queries: Survey study

Reference 78

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Observation 69436438-9b23-43a4-be7b-fb89cc96f202 · outbound

This paper cites What is polypharmacy? a systematic review of definitions.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions What is polypharmacy? a systematic review of definitions

Reference 79

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Observation a9f786b2-750d-4e48-89fa-f3f34afe33d8 · outbound

This paper cites AgentInstruct: Toward Generative Teaching with Agentic Flows.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions AgentInstruct: Toward Generative Teaching with Agentic Flows

Reference 80

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Observation d2ff18e4-b71d-494d-9808-164e2141f8e1 · outbound

This paper cites Extractive clinical question-answering with multianswer and multifocus questions: data set development and evaluation study.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Extractive clinical question-answering with multianswer and multifocus questions: data set development and evaluation study

Reference 81

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Observation 08537328-ff0b-4721-894a-6392eb0a1d04 · outbound

This paper cites Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe

Reference 82

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Observation 9d4793b3-7c7a-4d70-852d-4cbb41b8cff4 · outbound

This paper cites Llama 3.3 | Model Cards and Prompt formats — llama.com.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Llama 3.3 | Model Cards and Prompt formats — llama.com

Reference 83

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Observation d6dcbe7a-10fc-4a18-a1e3-763738e60872 · outbound

This paper cites Home - Gene - NCBI — ncbi.nlm.nih.gov.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Home - Gene - NCBI — ncbi.nlm.nih.gov

Reference 84

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Observation 01dce1ba-6a28-4a34-8307-fd1398db6464 · outbound

This paper cites OpenAI Platform — platform.openai.com.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions OpenAI Platform — platform.openai.com

Reference 85

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Observation ba0e0345-2d1a-480d-bbbc-f118a3cb81c5 · outbound

This paper cites Introducing GPT-4.1 in the API — openai.com.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Introducing GPT-4.1 in the API — openai.com

Reference 86

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Observation 65a72de6-cc83-4324-84cf-73bcc1c7f9f8 · outbound

This paper cites Neo4j Graph Database & Analytics – The Leader in Graph Databases — neo4j.com.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Neo4j Graph Database & Analytics – The Leader in Graph Databases — neo4j.com

Reference 87

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Observation b4fe3985-b5de-4f5b-9a28-bc2912f5891c · outbound

This paper cites an unresolved cited work.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 88

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Observation ea89251a-c612-4deb-afdc-37a0ca893e67 · outbound

This paper cites Bowman, and Shi Feng.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Bowman, and Shi Feng

Reference 89

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Observation 6d1bb59d-04d7-4e0d-bb43-4a50870ff85c · outbound

This paper cites Knowledge graph-based question answering with electronic health records.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Knowledge graph-based question answering with electronic health records

Reference 90

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Observation 2c2b92f2-92f1-4b1d-89da-89e71fabb525 · outbound

This paper cites OpenAI o3 and o4-mini System Card — openai.com.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions OpenAI o3 and o4-mini System Card — openai.com

Reference 91

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Observation bdbc5205-9231-4c36-adda-333a92837ca7 · outbound

This paper cites Spiqa: A dataset for multimodal question answering on scientific papers.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Spiqa: A dataset for multimodal question answering on scientific papers

Reference 92

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Observation f430f479-5fff-4928-8f14-3e66820ba2aa · outbound

This paper cites Line Notation (SMILES and InChI), aug 11 2020.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Line Notation (SMILES and InChI), aug 11 2020

Reference 93

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Observation 3a61898e-3d54-476c-9e6d-37db77c3c6f5 · outbound

This paper cites an unresolved cited work.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Unresolved cited work

Reference 94

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Observation 402b0e22-c86b-452e-a48f-6891e58620ed · outbound

This paper cites Coquad: a covid-19 question answering dataset system, facilitating research, benchmarking, and practice.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Coquad: a covid-19 question answering dataset system, facilitating research, benchmarking, and practice

Reference 95

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Observation dae75a50-dccf-4f6e-a25c-7d29afeaba55 · outbound

This paper cites Genetics: what is a gene? Nature, 441(7092), 2006.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Genetics: what is a gene? Nature, 441(7092), 2006

Reference 96

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Observation 28e5c924-6e83-47fd-85cc-67fa6d84bda9 · outbound

This paper cites Modeling relational data with graph convolutional networks.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Modeling relational data with graph convolutional networks

Reference 97

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Observation a6b5b791-8212-4fbf-99fc-d6f089dd4439 · outbound

This paper cites Introduction to informa- tion retrieval, volume 39.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions Introduction to informa- tion retrieval, volume 39

Reference 98

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Observation 449b6616-57f0-4683-9376-3f6e82c75289 · outbound

This paper cites SQuAD: 100,000+ questions for machine comprehension of text.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions SQuAD: 100,000+ questions for machine comprehension of text

Reference 99

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Observation 15d655ac-fedb-47ab-85ad-394abd6b96e8 · outbound

This paper cites sentence-transformers/all-MiniLM-L6-v2 · Hugging Face — hugging- face.co.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions sentence-transformers/all-MiniLM-L6-v2 · Hugging Face — hugging- face.co

Reference 100

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Observation 4176a2e0-c2d4-4cf1-a69a-e61e46ac4475 · outbound

This paper cites User prompts vs.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions User prompts vs

Reference 101

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Observation 57f1adc0-8128-443e-a930-6c0734668db7 · outbound

This paper cites LexicalRichness: A small module to compute textual lexical richness, 2022.

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions LexicalRichness: A small module to compute textual lexical richness, 2022

Reference 102

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Pith citing papers

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