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Paper Citation Record · LEDGER

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge

As of 12 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2412.08317.

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

pith.paper-citation-record.v1
2412.08317 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:59:43.730357Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

  • verified exact2
  • verified fuzzy20
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6883639-2257-4285-8fca-ded033949def · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 1

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no resolver link, observed 2026-08-11T17:59:43.499363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.499363Z digest=sha256:79291ea7975517dfce90afabc9f37cc92678be89a4e4a10247694f2c90c8a2cf

Observation 7a47b91a-7585-4c5f-b41a-03fb3fcabc34 · outbound

This paper cites Language models are unsupervised multitask learners.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Language models are unsupervised multitask learners

Reference 2

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no resolver link, observed 2026-08-11T17:59:43.505737Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.505737Z digest=sha256:e0536eb15c6a0ba7ec1c0b7bcba184d1503909420bd703e0ee6f6eedf328862c

Observation 9c0f45f4-1dd8-48b5-94e3-eedd21da5d81 · outbound

This paper cites Xlnet: Generalized autoregressive pretraining for language understanding.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Xlnet: Generalized autoregressive pretraining for language understanding

Reference 3

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raw_fallback, observed 2026-08-11T17:59:44.575978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.511009Z digest=sha256:787a5046ee5ebb9be86a8b2b5b273f234fee02bc664147c3e2ad8da358815c4b

Observation b4f347d4-1ab8-4c80-a1bb-b70d145284f2 · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 4

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no resolver link, observed 2026-08-11T17:59:43.516670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.516670Z digest=sha256:114ca0ab05d099425f99c6ad966e7533bff1e767ffe6539ecb348c04b7bd7014

Observation d88651c2-7adf-44b7-bb58-47da6f725f01 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 5

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no resolver link, observed 2026-08-11T17:59:43.523394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.523394Z digest=sha256:5f02548a3a785e8a64e447cbc58837efbe9d053108c8198c333eeac8e99788f1

Observation f3900d4c-055f-4359-a1b7-898571e4c6d4 · outbound

This paper cites Language models are few-shot learners.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Language models are few-shot learners

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e6f6c06e-4575-4c7b-ac9c-0a4a69a0995e · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.543038Z digest=sha256:cc23ad014a1db632ae5cee1dd93c74e4f30f4e062099e2a6205ff95a1e50bad9

Observation d765eae1-ddb0-4782-b0c2-a3a13cf56717 · outbound

This paper cites GPT-4 Technical Report.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge GPT-4 Technical Report

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.551741Z digest=sha256:16b4bf23c4b15a720a84d3ef9a28037def7f44f76c65dda9fe521949a954a0e0

Observation 5325a93a-e7b6-4d4f-9a2a-77862ebc3024 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Chain-of-thought prompting elicits reasoning in large language models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.558197Z digest=sha256:c6a51e717a912c370ed48d3eefbff31516f855c720d83bfdadb99641a9e91eb2

Observation 053e3a50-9c2b-4349-842c-edb560e99241 · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.562900Z digest=sha256:d31283412337c11c0d9af4f484ca78aca7c718bb15839c6cefe9546a0a603e3f

Observation 688239ba-3ed7-4a42-8dfb-5919bace4314 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Tree of thoughts: Deliberate problem solving with large language models

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.568293Z digest=sha256:a58f75cfc306c165322941f4949cf079fd6c2a86743dad84774a71a3b8b9fba7

Observation 21f7fa33-c3e7-4c38-8561-bc1184864ed0 · outbound

This paper cites Multi-hop Question Answering.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Multi-hop Question Answering

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.572557Z digest=sha256:2699119122266759c3dd1df99134c26453ba94d32cb839324e22d8f40e630daa

Observation 64b67027-4036-430d-b6d8-ce3962e0037c · outbound

This paper cites Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study

Reference 13

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verified exact
local_arxiv, observed 2026-08-11T17:59:43.946976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.578293Z digest=sha256:08fc6fdafa63ff38458e50733e78c9dfa836b72219cce864b2c59c0c0ca4a7ad

Observation 07493ef8-73c3-4596-9c6f-5cd4b7f90ef8 · outbound

This paper cites Edge-aware graph neural network for multi-hop path reasoning over knowledge base.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Edge-aware graph neural network for multi-hop path reasoning over knowledge base

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.456432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.583163Z digest=sha256:9bfa45110e10e16332f10286635152281ee93944d8116c294e415dee193edc1a

Observation 949f16d5-308b-4226-bbba-2212d1293033 · outbound

This paper cites Knowledge-enhanced iterative instruction generation and reasoning for knowledge base question answering.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Knowledge-enhanced iterative instruction generation and reasoning for knowledge base question answering

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.439978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.588822Z digest=sha256:de78b985e0bd689f197074434d342af0cbd0b294549d12b6f6cce216f128b348

Observation f5a3654c-d123-437f-8e55-8c797f8abd09 · outbound

This paper cites Stepwise relation prediction with dynamic reasoning network for multi-hop knowledge graph question answering.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Stepwise relation prediction with dynamic reasoning network for multi-hop knowledge graph question answering

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.412528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.594703Z digest=sha256:5ea5f8f6aece632b2a9910e6f0f1e68dc5b7000517c0297f0b252315ef822169

Observation aa8be2df-7ea6-491a-b9bd-f6e65ee0e0fb · outbound

This paper cites Multi-hop question answering using sparse graphs.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Multi-hop question answering using sparse graphs

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.387895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.599979Z digest=sha256:dc5fd25df1f3170d3eeadf4dc5235f1c9e97784424eabf5b65973d9dd90cec72

Observation cb05e7d5-26fe-4ae5-ae32-ed156aa0bd8b · outbound

This paper cites Answering complex open-domain questions with multi-hop dense retrieval.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Answering complex open-domain questions with multi-hop dense retrieval

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.370023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5233565c-e7df-4cd5-bc8a-6722c4aa1cfd · outbound

This paper cites Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-11T17:59:43.914873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.613499Z digest=sha256:70ad9aed24d75f6126d0ab13d96f7375876d70ba8560805be5dc0172981a3f7a

Observation 942cff6e-aac2-4e32-baac-cab212023f1c · outbound

This paper cites Triple-fact retriever: An explainable reasoning retrieval model for multi-hop qa problem.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Triple-fact retriever: An explainable reasoning retrieval model for multi-hop qa problem

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.344408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.619287Z digest=sha256:423f3ab26f4a7868e59b19e7e7cf04e975e1f955ec8c2bc867a5d140edaed9bf

Observation 960aae48-8d81-43f7-a8bc-c6bd68aad679 · outbound

This paper cites Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e4671539-3b61-4541-98f6-5b5f0d324bda · outbound

This paper cites Entailment as Few-Shot Learner.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Entailment as Few-Shot Learner

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.632242Z digest=sha256:34b854050fe6ff66809e55581dc51013a889992f589cdbc215cb66af7b5d222e

Observation 415701e6-b996-41e5-b3d7-4f0ac11664b7 · outbound

This paper cites Multi-hop reading comprehension through question decomposition and rescoring.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Multi-hop reading comprehension through question decomposition and rescoring

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.319810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.636209Z digest=sha256:33f9f81cf130a06465cd477d75c40e61dded382451340ac770d3b0ce1651c7e9

Observation 55679171-bf43-47b8-91fe-11bd1b5931be · outbound

This paper cites Measuring and narrowing the compositionality gap in language models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Measuring and narrowing the compositionality gap in language models

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.301300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 4b5482f6-c0ac-4b97-8eac-6d19b62d6869 · outbound

This paper cites Tree-of-reasoning question decomposition for complex question answering with large language models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Tree-of-reasoning question decomposition for complex question answering with large language models

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.283813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.644318Z digest=sha256:2aa0f7d1d11a8873f1f21b8802632b5c8ba0e0ba70bbefa7d633d54f90d2bfbb

Observation 40c9f1f1-3859-419c-a15d-498d549e3a40 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 26

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no resolver link, observed 2026-08-11T17:59:43.648142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.648142Z digest=sha256:94e5bfddf9d6112079e2898e9474bf9ad2e14cd3fdba5bb5df842435d156d53b

Observation 298a36e2-60a6-4b97-ac41-7b8a6efed934 · outbound

This paper cites A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

Reference 27

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no resolver link, observed 2026-08-11T17:59:43.653704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.653704Z digest=sha256:566fa2d03d8695ad7fc09c778d0635bd001a88d280c60250218b8e7d581fe2c5

Observation 3812181d-5493-411d-a8e8-584935160f7a · outbound

This paper cites Dai, and Quoc V Le.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Dai, and Quoc V Le

Reference 28

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no resolver link, observed 2026-08-11T17:59:43.658542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.658542Z digest=sha256:fb12fe399f6b1628e3ba2c159645375d89fa01ed21a9e6997ea0dac78bdd3044

Observation 850b983d-aa7f-4782-8c84-312582c38059 · outbound

This paper cites Multitask prompted training enables zero-shot task generalization.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Multitask prompted training enables zero-shot task generalization

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.254373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.663106Z digest=sha256:8ade06a0f6d484dcc7e3d3776d5a9420e97e6a44bd8f95962369e6b7aa37bd51

Observation c0951306-9f93-47b5-b107-022eae28f9f6 · outbound

This paper cites Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou

Reference 30

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no resolver link, observed 2026-08-11T17:59:43.667896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.667896Z digest=sha256:e7782b86b0157a855d7b8a36985bb4aef2392fcc39be73acc9614c33c8557cae

Observation bd8bb1b8-9415-4a54-a585-0dcf44d11229 · outbound

This paper cites Large language models are zero-shot reasoners.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Large language models are zero-shot reasoners

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.225479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.674623Z digest=sha256:c6a33c08801a9bd6b68b3087abdf400313a77c65144132fdb1a45f6caefec6dd

Observation 0c3802af-f36c-44b2-97bf-d654e7dd4764 · outbound

This paper cites Selection-inference: Exploiting large language models for interpretable logical reasoning.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Selection-inference: Exploiting large language models for interpretable logical reasoning

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T17:59:43.679344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.679344Z digest=sha256:988f58eb6c34edbc368b3aa436ad534c8d69666fb28deb94ed6c34b4631dcadc

Observation 2faa014d-a9d1-43b9-8af9-f590367f3632 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge React: Synergizing reasoning and acting in language models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T17:59:43.683777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.683777Z digest=sha256:6c3cc60921253fbc140cc151a4c4eaded41b8c6b0ef21516fd390102762fa57b

Observation 2b0eba2a-f3ec-4c25-88d4-6cd4aa11d925 · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-11T17:59:44.186470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.689698Z digest=sha256:ec8b52fc2a2d5e11135214973b9f22e679c81350cb697da6be9deff902b0f684

Observation 55666112-3198-41dd-99f1-191aa0fd795c · outbound

This paper cites Explaining answers with entailment trees.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Explaining answers with entailment trees

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.167865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.694266Z digest=sha256:1adc625fc39b20ecf61e85a44fdb3f5898be9208f591eec634d61a47513e21d1

Observation b57dc65c-f7a6-46ac-946b-cc8ac72fc033 · outbound

This paper cites Qasc: A dataset for question answering via sentence composition.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Qasc: A dataset for question answering via sentence composition

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.152616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.700201Z digest=sha256:d74ee2d90f29b76d8bcc51f9b9ebb1b92f38a1d8b6ec22f300f4390bcb200347

Observation 78274a6f-2337-4d8a-a9c7-fe9a743879ac · outbound

This paper cites Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T17:59:43.705384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:59:43.705384Z digest=sha256:48860f971cbef341ff77557fdec9f565e24c9cde58efe422c8d1cf97a78f4a09

Observation 6be2f1be-b3d7-4217-8269-a6a2162eb88a · outbound

This paper cites Cognitive neuroscience of human counterfactual reasoning.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Cognitive neuroscience of human counterfactual reasoning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.133854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.710391Z digest=sha256:478aeff559cbc600fde0e0d729921e9ed2cf13485909929bbab950b563ffd767

Observation a65c2047-cede-4f45-a9b2-dfacee181553 · outbound

This paper cites Do large language models know what they don’t know? In Findings of the Association for Computational Linguistics: ACL 2023, pages 8653–8665, 2023.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Do large language models know what they don’t know? In Findings of the Association for Computational Linguistics: ACL 2023, pages 8653–8665, 2023

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.106339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.715040Z digest=sha256:760c5b046e8d5602a1d36bc88bc9f285e12f750ebfe0524f77423b2130adbaca

Observation 477c8e5f-7638-44ab-948a-9f292c007ee3 · outbound

This paper cites A study of automatically acquiring explanatory inference patterns from corpora of explanations: Lessons from elementary science exams.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge A study of automatically acquiring explanatory inference patterns from corpora of explanations: Lessons from elementary science exams

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T17:59:44.083995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.720043Z digest=sha256:2282424b17f25fd777ecc809125a9e4f2729e510913490a76fbf1603d7032159

Observation 55889101-0cbc-4ffb-9400-5b40dbcabc04 · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-11T17:59:44.063216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.725569Z digest=sha256:5b8780b5a60ff13a1a9169efa7318b318c2990d3dbf64c8d8490ff74cd1d5644

Observation 222459f9-1b3d-46f3-92cd-d33518877bc8 · outbound

This paper cites an unresolved cited work.

Large Language Models Still Face Challenges in Multi-Hop Reasoning with External Knowledge Unresolved cited work

Reference 2010

Resolution
unresolved
raw_fallback, observed 2026-08-11T17:59:44.045135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T17:59:43.730357Z digest=sha256:0f0bfae7ae367bde08902f4d82ee019bd9aa6b30cd7d5c695bc949bf350bad86

Pith citing papers

No inbound Pith citation observations are available.