Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:08:27.681538Z
Paper Citation Record · LEDGER
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study
As of 17 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 3 inbound Pith citation observations for arXiv:2504.16414.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T07:36:16.071678Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
53 of 53 outbound references displayed
- verified exact0
- verified fuzzy17
- unresolved35
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- malformed identifier1
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External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 5c5e6c69-650d-4882-aaa5-87e6b52bbe80 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Chain-of-thought prompting elicits reasoning in large language models
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 786957e3-11ee-4bd9-8cf6-b17ab453974b · outbound
This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 2
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 944effd2-5832-4a98-a42d-1168409c548c · outbound
This paper cites Tree of thoughts: Deliberate problem solving with large language models.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Tree of thoughts: Deliberate problem solving with large language models
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32f29f2b-c9a0-4b7c-921d-153931ba86ab · outbound
This paper cites Graph of thoughts: Solving elaborate problems with large language models.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Graph of thoughts: Solving elaborate problems with large language models
Reference 4
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 13d59eb0-efc0-4df1-b3e2-b9aa560dd2f3 · outbound
This paper cites Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought
Reference 5
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a7b19a6c-a234-4bdc-ae53-5b648bc62361 · outbound
This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Retrieval-augmented generation for knowledge-intensive nlp tasks
Reference 6
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6a74663-37b9-4855-9319-3a2c3aa1ec46 · outbound
This paper cites Neurosymbolic ai: the 3rd wave.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Neurosymbolic ai: the 3rd wave
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9d08a5c9-624c-448b-99f9-32434f31f4a2 · outbound
This paper cites A simple neural network module for relational reasoning.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study A simple neural network module for relational reasoning
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:08:27.093328Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97572626-9b5c-4b01-8063-0926d91a566f · outbound
This paper cites Openai o1 system card, 2024.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Openai o1 system card, 2024
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:08:30.352691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6cc56a61-3388-4dce-a4a6-828a2c935406 · outbound
This paper cites Openai o3 mini system card, 2024.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Openai o3 mini system card, 2024
Reference 10
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 66bfd8a0-6bde-405b-a898-8e781124fff6 · outbound
This paper cites Star: Bootstrapping reasoning with reasoning.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Star: Bootstrapping reasoning with reasoning
Reference 11
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3fa5a002-6426-4f1f-831d-0a6aaf77bba8 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 12
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29e29159-c387-401a-ac6e-a105ab72a4c6 · outbound
This paper cites Advancing Reasoning in Large Language Models: Promising Methods and Approaches.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Advancing Reasoning in Large Language Models: Promising Methods and Approaches
Reference 13
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b230e105-f40e-4ff2-841c-8136172dd967 · outbound
This paper cites Training Verifiers to Solve Math Word Problems.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Training Verifiers to Solve Math Word Problems
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24e21779-dfdd-4895-b1b4-90719cd3759b · outbound
This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Measuring Mathematical Problem Solving With the MATH Dataset
Reference 15
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82536658-847e-4cb7-b819-fb84870c44b8 · outbound
This paper cites Evaluating Large Language Models Trained on Code.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Evaluating Large Language Models Trained on Code
Reference 16
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9204ca91-0a5e-4a88-8c70-8adb6cb214de · outbound
This paper cites Program Synthesis with Large Language Models.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Program Synthesis with Large Language Models
Reference 17
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf725a04-e15f-44d4-a024-f57cc3f71d37 · outbound
This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 740f52cd-73f3-4f59-a006-42bdbc301f89 · outbound
This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a88ce35-5293-4571-ab1c-c47953128198 · outbound
This paper cites Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Reference 20
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06b0d660-6999-4e5d-bc64-5b22630fae49 · outbound
This paper cites Chemlit-qa: A human evaluated dataset for chemistry rag tasks.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Chemlit-qa: A human evaluated dataset for chemistry rag tasks
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e907d867-c733-4885-97e2-288143e5a7a0 · outbound
This paper cites OlympicArena Medal Ranks: Who Is the Most Intelligent AI So Far?.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study OlympicArena Medal Ranks: Who Is the Most Intelligent AI So Far?
Reference 22
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7f7b64c-6296-4cbc-bb26-b4ab59c56f40 · outbound
This paper cites Gpqa: A graduate-level google-proof q&a benchmark.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Gpqa: A graduate-level google-proof q&a benchmark
Reference 23
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8236d33-6d50-4e29-9cec-efee71ba2911 · outbound
This paper cites Large language models for reticular chemistry.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Large language models for reticular chemistry
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 36a26e47-c694-4748-9e8d-ca759c55071e · outbound
This paper cites Multi-hop question answering.Foundations and Trends® in Information Retrieval, 17(5):457–586, 2024.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Multi-hop question answering.Foundations and Trends® in Information Retrieval, 17(5):457–586, 2024
Reference 25
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b5031814-288e-4a46-a47c-b1f0504b416d · outbound
This paper cites Constructing datasets for multi-hop reading comprehension across documents.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Constructing datasets for multi-hop reading comprehension across documents
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9d0f70dd-d8b9-4988-9160-e4680425be07 · outbound
This paper cites Musique: Multihop questions via single-hop question composition.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Musique: Multihop questions via single-hop question composition
Reference 27
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dbc7d224-0086-49fc-94a0-00d046a57c52 · outbound
This paper cites MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries
Reference 28
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e491458-4e77-48f0-840e-19e2a3c7e46a · outbound
This paper cites A framework for evaluating the chemical knowledge and reasoning abilities of large language models against the expertise of chemists.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study A framework for evaluating the chemical knowledge and reasoning abilities of large language models against the expertise of chemists
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8ccf9fa0-2b60-46a4-ae87-028672acace6 · outbound
This paper cites Knowledge Graph Generation From Text.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Knowledge Graph Generation From Text
Reference 30
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 52d9b364-0a8c-4870-afbd-052a4e0e89e6 · outbound
This paper cites Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction
Reference 31
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0c10439b-070b-4430-866b-dc528a1dd822 · outbound
This paper cites Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
Reference 32
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba8d481d-d409-4b24-8b71-6407539fcf87 · outbound
This paper cites CEAR: Automatic construction of a knowledge graph of chemical entities and roles from scientific literature.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study CEAR: Automatic construction of a knowledge graph of chemical entities and roles from scientific literature
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1ac075f-247c-4ed7-bd18-ba773281e3b5 · outbound
This paper cites Coarse-to-fine knowledge graph domain adaptation based on distantly-supervised iterative training.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Coarse-to-fine knowledge graph domain adaptation based on distantly-supervised iterative training
Reference 34
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5576a2ae-05d5-4cc1-b051-9616aaf09c2f · outbound
This paper cites Nilinker: attention-based approach to nil entity linking.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Nilinker: attention-based approach to nil entity linking
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation da72f682-ae47-4430-aec0-92ac7fb792b6 · outbound
This paper cites Domain-specific language model pretraining for biomedical natural language processing, 2020.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Domain-specific language model pretraining for biomedical natural language processing, 2020
Reference 36
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fb675f9-8468-4f99-8af4-6e5a5aa47793 · outbound
This paper cites Pubchem in 2021: new data content and improved web interfaces.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Pubchem in 2021: new data content and improved web interfaces
Reference 37
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2436015d-32bf-4163-bba8-422f32711f77 · outbound
This paper cites Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering
Reference 38
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32c19761-3314-44f5-9941-174a5c16880e · outbound
This paper cites Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering
Reference 39
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 421bf404-e7fa-49fc-851e-293c94ef9bd2 · outbound
This paper cites HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation
Reference 40
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1a2e9e7-84bb-4fd1-993c-d390a5c8f5d1 · outbound
This paper cites If an entity appears in the text but has no meaningful chemical relationship with another entity in the set, ignore it.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study If an entity appears in the text but has no meaningful chemical relationship with another entity in the set, ignore it
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:08:29.292668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f1c16554-379c-4678-a088-4ba9c7626a5b · outbound
This paper cites reacts with,.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study reacts with,
Reference 42
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 798ee359-8162-46fb-bcad-67cfede7a0ae · outbound
This paper cites Avoid observations, opinions, and findings.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Avoid observations, opinions, and findings
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:08:29.133824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 43c2180b-0fd6-48b7-b3cf-fe615e51a8b6 · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 44
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:29.013438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ce6a1cbe-346f-4bc0-b870-e256db6e8ae0 · outbound
This paper cites is," "are,.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study is," "are,
Reference 45
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-16T11:08:28.936126Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 92e7b5b1-7d25-4811-bb54-ede837e6e937 · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.830681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2399d8b1-ad29-420e-9761-98510f168c3a · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.737345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cc2f68e7-ea64-42c1-a70d-759ebd42b168 · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 48
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.625815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 553dea26-92c7-4f1a-b04b-e8b0689bdf64 · outbound
This paper cites Path (multi-hop chain of reasoning): carbon dioxide → formic acid → carbonylation reactions * Source 1 and source 2 are coming from different documents.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Path (multi-hop chain of reasoning): carbon dioxide → formic acid → carbonylation reactions * Source 1 and source 2 are coming from different documents
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:08:28.560799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 243384e8-1122-4e3f-a7ae-2c24014fd39b · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 50
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.465748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 034087ee-1c86-4b52-985c-2fd3ea838638 · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.390841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 178c6e3d-e52b-4415-a339-25f1f22d0379 · outbound
This paper cites an unresolved cited work.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T11:08:28.340057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6a04d0a5-cf6c-430a-ae55-36855dfef0b2 · outbound
This paper cites Path (multi-hop chain of reasoning): solution → graphene → membranes→ nitrogen→ Cr3(Cr4Cl)3(BTT)82 *Sources 1–4 are extracted from four different documents.
Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study Path (multi-hop chain of reasoning): solution → graphene → membranes→ nitrogen→ Cr3(Cr4Cl)3(BTT)82 *Sources 1–4 are extracted from four different documents
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:08:28.270081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
Observation 21c4f34c-9e8a-4df6-9b7f-669d779d9684 · inbound
When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering cites this paper.
When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T10:32:44.995439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1693f0ed-7475-441d-9649-716484bb71d1 · inbound
When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering cites this paper.
When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T07:36:16.071678Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03480b6e-f309-4b1a-ab25-7a48a7342950 · inbound
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes cites this paper.
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes Evaluating Multi-Hop Reasoning in Large Language Models: A Chemistry-Centric Case Study
Reference 116
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T13:00:55.949775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.