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Paper Citation Record · LEDGER

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding

As of 20 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2607.29196.

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

pith.paper-citation-record.v1
2607.29196 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:54:22.116161Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

68 of 68 outbound references displayed

  • verified exact6
  • verified fuzzy0
  • unresolved62
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0cf0ce2-41e3-4d47-94db-1bd806f57502 · outbound

This paper cites Alibaba Cloud Model Studio : Model list.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Alibaba Cloud Model Studio : Model list

Reference 1

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source=arxiv_source observed=2026-08-03T11:54:15.919993Z digest=sha256:7ab7954d4427802caf6a012e41c64b6fff82c092491db370b98f75798bf3c1f3

Observation 3036ea58-a18b-4e08-97a5-cef77ef32811 · outbound

This paper cites Claude Platform : Models overview.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Claude Platform : Models overview

Reference 2

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source=arxiv_source observed=2026-08-03T11:54:16.042870Z digest=sha256:70f61f145f85c4f33cfccc94d324d2428f6f7f893dc68f56d5f3288027f6855d

Observation 14bbb043-3dbf-43a8-9f36-822884196317 · outbound

This paper cites MT-Bench-101 : A fine-grained benchmark for evaluating large language models in multi-turn dialogues.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding MT-Bench-101 : A fine-grained benchmark for evaluating large language models in multi-turn dialogues

Reference 3

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source=arxiv_source observed=2026-08-03T11:54:16.153590Z digest=sha256:2825a9f084c131328312cd7fc63dd9e2eb2763393e586fdc5d62c5ba755f3d2e

Observation d9b935d4-89b7-464c-9b93-81d198d4a8ec · outbound

This paper cites Doubao Seed Models : Model documentation.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Doubao Seed Models : Model documentation

Reference 6

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source=arxiv_source observed=2026-08-03T11:54:16.411559Z digest=sha256:b1f390acfe2eeef1adea220062e64b84d7b43643c6052c97890e824493a89634

Observation 7651d1cd-8161-475a-a40c-395242d3ee08 · outbound

This paper cites DeepSeek API Docs : Models and pricing.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding DeepSeek API Docs : Models and pricing

Reference 7

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source=arxiv_source observed=2026-08-03T11:54:16.444735Z digest=sha256:6295e029dc7a52b2f2c9f000357753023f35dec5f6b9b488051603046ef0032f

Observation a833b0b0-d3ad-4cd8-9de6-45b8972cce1e · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 10

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source=arxiv_source observed=2026-08-03T11:54:16.537617Z digest=sha256:58a0ae998b6c2a4d5d4f392117cf5ef331a1e5cee36354924946f7c574257b6d

Observation 1912a822-75cb-469e-9841-64c175ed4af3 · outbound

This paper cites FairMT-Bench : Benchmarking fairness for multi-turn dialogue in conversational LLMs.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding FairMT-Bench : Benchmarking fairness for multi-turn dialogue in conversational LLMs

Reference 11

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source=arxiv_source observed=2026-08-03T11:54:16.559431Z digest=sha256:63eb49c3e16586b0ff9e479fa73aa13114307925c6b884a382bde1b5cd1f3abe

Observation 603b541b-59bc-4471-8346-954d49da2f21 · outbound

This paper cites Gemini API : Models.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Gemini API : Models

Reference 12

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source=arxiv_source observed=2026-08-03T11:54:16.629039Z digest=sha256:916a93d98be6d114161fa6b2d81030f8158ec4bb00942055c656f8b02d068533

Observation 44f2f3a2-e09c-4f37-ae59-dc1b28bd6b3e · outbound

This paper cites RULER : What's the real context size of your long-context language models? In COLM, 2024.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding RULER : What's the real context size of your long-context language models? In COLM, 2024

Reference 16

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source=arxiv_source observed=2026-08-03T11:54:16.923948Z digest=sha256:0fe60ccc62b92891ce374ad296c0c6c27d5e13f75e4d2b0d3e4e6e4a5fb10c3d

Observation 66ffa153-03d6-482a-9884-32961603557e · outbound

This paper cites FollowBench : A multi-level fine-grained constraints following benchmark.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding FollowBench : A multi-level fine-grained constraints following benchmark

Reference 18

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source=arxiv_source observed=2026-08-03T11:54:16.974012Z digest=sha256:90747934abcb36cc05325e15366c888dd8d44473f242b7032ed93c884dae9ed6

Observation 3f177cc6-b26d-4473-a42d-157813d9b8a4 · outbound

This paper cites BABILong : Testing the limits of LLMs with long context reasoning-in-a-haystack.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding BABILong : Testing the limits of LLMs with long context reasoning-in-a-haystack

Reference 19

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source=arxiv_source observed=2026-08-03T11:54:17.019149Z digest=sha256:bb8ab5fe99eee0e85d92d6ab3185229866c7369f042c3743ad8a815586213b51

Observation 4dac1aa8-5421-400a-bc94-1ada3ffefbe2 · outbound

This paper cites MT-Eval : A multi-turn capabilities evaluation benchmark for large language models.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding MT-Eval : A multi-turn capabilities evaluation benchmark for large language models

Reference 20

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source=arxiv_source observed=2026-08-03T11:54:17.079136Z digest=sha256:d22fd4893167a3d1b5ef75447623819d868eaef75e15d61021dd0a43ab1e3996

Observation cb74a53b-6413-47a3-b470-73366c7fbefa · outbound

This paper cites LLMs get lost in multi-turn conversation.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding LLMs get lost in multi-turn conversation

Reference 21

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source=arxiv_source observed=2026-08-03T11:54:17.128350Z digest=sha256:570783469e4f87a1c0bad2abc04524dc873e0bdce26a8a1660c52057c0d3d3b9

Observation 356376a1-a280-4d92-9ea9-2752420a64f7 · outbound

This paper cites Gonzalez, and Ion Stoica.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Gonzalez, and Ion Stoica

Reference 23

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source=arxiv_source observed=2026-08-03T11:54:17.180556Z digest=sha256:9ddf4d1f93dea61592466e8bee9bb60e357722df3c2090aa0ea7824b3b1c009a

Observation 8c8549df-01c6-4de3-8f02-dc5573d5c8f6 · outbound

This paper cites WildBench : Benchmarking LLMs with challenging tasks from real users in the wild.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding WildBench : Benchmarking LLMs with challenging tasks from real users in the wild

Reference 26

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source=arxiv_source observed=2026-08-03T11:54:17.357756Z digest=sha256:b020c0f1bd2711eca28436db0122cd196ed8d020b9fe5b37f9ec8b2e7fe898f0

Observation 27475f7e-b596-469f-8cf3-24a2093494e1 · outbound

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

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Lost in the middle: How language models use long contexts

Reference 27

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source=arxiv_source observed=2026-08-03T11:54:17.413746Z digest=sha256:047f26b4006d45afa6ec3204e2acb22912345b02db9a1a9d92dad708821a4019

Observation 4d45c391-a5f7-4eee-b4f9-324475eba6fe · outbound

This paper cites AgentBench : Evaluating LLMs as agents.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding AgentBench : Evaluating LLMs as agents

Reference 29

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source=arxiv_source observed=2026-08-03T11:54:17.559077Z digest=sha256:a2a6175974d71561fba6cca1136c936932c6dfbe472e731ebc290d6488a95aab

Observation f89319d8-1197-4fa1-a93e-a123ac6a6de0 · outbound

This paper cites an unresolved cited work.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Unresolved cited work

Reference 30

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source=arxiv_source observed=2026-08-03T11:54:17.602223Z digest=sha256:5840d8bc16ed15d369ca622abcb541070fed4804e6b4ec1b18fc2c39a86ec5a1

Observation d2cbc0fe-42c2-40ad-a71c-ddbb8be256c7 · outbound

This paper cites Kimi API Platform : Model list.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Kimi API Platform : Model list

Reference 31

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source=arxiv_source observed=2026-08-03T11:54:17.702021Z digest=sha256:3c26df3872266cd2abcedbf91e18dbb9f97fc23b43b5a572463f707bd0fc3d12

Observation 629ab9e0-4056-45b6-8456-a44fcfe905c9 · outbound

This paper cites OpenAI Platform : Models.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding OpenAI Platform : Models

Reference 32

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source=arxiv_source observed=2026-08-03T11:54:17.768866Z digest=sha256:871a650c97e98e1e33f21ffed3eb98b1cf39cebdbcc1cc6ed37057632f5d1ee8

Observation 5a1e23ee-283c-43d4-90a7-dec9d6524afa · outbound

This paper cites Hy3 and Hy3 Preview : Model repositories.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Hy3 and Hy3 Preview : Model repositories

Reference 36

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source=arxiv_source observed=2026-08-03T11:54:18.233562Z digest=sha256:f49787b0e93cebdc111413b478d05c96101a4b8a9c8f13055f6774943a0c8332

Observation d19327f9-2842-4873-8fcb-988fe0aa84bf · outbound

This paper cites CMT-Eval : A novel chinese multi-turn dialogue evaluation dataset addressing real-world conversational challenges.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding CMT-Eval : A novel chinese multi-turn dialogue evaluation dataset addressing real-world conversational challenges

Reference 37

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source=arxiv_source observed=2026-08-03T11:54:18.265099Z digest=sha256:874dc0de95229a40d108d30dbc0b9e0fa135f9436d5930faeb250aa195862ed7

Observation 473381da-46c6-4d6b-8945-b2c2423d20b1 · outbound

This paper cites MINT : Evaluating LLMs in multi-turn interaction with tools and language feedback.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding MINT : Evaluating LLMs in multi-turn interaction with tools and language feedback

Reference 38

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source=arxiv_source observed=2026-08-03T11:54:18.345350Z digest=sha256:b94a1d22c6821b5377ee061d23aa7a1b381372116427dfc62a38b9c850f08266

Observation 261179f1-6dc4-4b9c-aa60-3b2d90ab4d01 · outbound

This paper cites Benchmarking complex instruction-following with multiple constraints composition.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Benchmarking complex instruction-following with multiple constraints composition

Reference 39

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source=arxiv_source observed=2026-08-03T11:54:18.451885Z digest=sha256:0646ba49f7ba3bab6e268e2e56b4bc2505bc6a0b658d60d2bce69a3519e1b7c0

Observation 44b14624-421e-491f-a8e4-dc2900169b7b · outbound

This paper cites LongMemEval : Benchmarking chat assistants on long-term interactive memory.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding LongMemEval : Benchmarking chat assistants on long-term interactive memory

Reference 40

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source=arxiv_source observed=2026-08-03T11:54:18.560017Z digest=sha256:e2975de671a8c39b5118bd6a7c6e2092c3cc0dde4948a8ba0b3720290b552c6b

Observation 9a66bbfe-6b56-46ae-b77e-b38b002879c1 · outbound

This paper cites xAI API : Models (grok 4.5).

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding xAI API : Models (grok 4.5)

Reference 41

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source=arxiv_source observed=2026-08-03T11:54:18.613923Z digest=sha256:0fd249e6249e98b35ec1e19e3fdfd337378464923fc759878ef757bf9e4d27e2

Observation 412a0b53-379d-465a-bf0e-f6e05dca639f · outbound

This paper cites Evaluating large language models at evaluating instruction following.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Evaluating large language models at evaluating instruction following

Reference 42

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source=arxiv_source observed=2026-08-03T11:54:18.721000Z digest=sha256:7327b6434b9d317b0f1e5c1beb0f9bcbb89c135e7e79ccbb1ce54c56053564e1

Observation f16b115b-90fe-40c0-8776-b6dc2acfc2e8 · outbound

This paper cites IHEval : Evaluating language models on following the instruction hierarchy.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding IHEval : Evaluating language models on following the instruction hierarchy

Reference 44

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source=arxiv_source observed=2026-08-03T11:54:18.888898Z digest=sha256:30805baa3c62ce0bdad6c2a56ac03f7c83d3fd3bc5832e3f7aa4e9a98c8c0789

Observation 74defae4-0169-4498-85d2-ef0f1bb937c2 · outbound

This paper cites Judging LLM -as-a-judge with MT-Bench and chatbot arena.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Judging LLM -as-a-judge with MT-Bench and chatbot arena

Reference 45

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source=arxiv_source observed=2026-08-03T11:54:19.008449Z digest=sha256:e773dd61d8c2faa9d8e74c29c513b49b90d00a8df400a8e251da3cd6a03eaf55

Observation 6598612d-71c5-4a06-ba10-f913903dca20 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Instruction-Following Evaluation for Large Language Models

Reference 47

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source=arxiv_source observed=2026-08-03T11:54:19.138575Z digest=sha256:117865f4623d9a7cceb8bb61f47850a492dd2da9bf2ca673029ad457ced8e248

Observation 95e2234a-e055-442d-9436-52831b1a6544 · outbound

This paper cites an unresolved cited work.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Unresolved cited work

Reference 48

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source=arxiv_source observed=2026-08-03T11:54:19.193063Z digest=sha256:54c57e46321a55d983c9b07b8837705a6a70fb8ebcaeb005dd7e2806237af38d

Observation 1c203874-00cb-471a-998d-4c739198b33d · outbound

This paper cites 2024 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , doi=

Reference 49

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source=arxiv_source observed=2026-08-03T11:54:19.334819Z digest=sha256:a3173d9e98cee7025eb13a560bba990242bb59e50503f970b41b174aa96a57f7

Observation f7682089-71b1-42e1-8b75-7dfa8245a5a6 · outbound

This paper cites 2024 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , doi=

Reference 50

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source=arxiv_source observed=2026-08-03T11:54:19.445605Z digest=sha256:250e929c10c1ee8b7e8a6083854279b721ec71a01abd5e98a25df5c1b13727de

Observation 3ce27f70-24a4-4c64-89b2-5b147d3a0374 · outbound

This paper cites Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following

Reference 51

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source=arxiv_source observed=2026-08-03T11:54:19.499279Z digest=sha256:f70fd3574e69c267a4a53b92f0ca16e273c5600eec327706f9f50c0cf148ba80

Observation 6ad40d67-b1b2-47e9-9524-66dc83fa7371 · outbound

This paper cites 2026 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2026 , url=

Reference 52

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source=arxiv_source observed=2026-08-03T11:54:19.553312Z digest=sha256:7baf27d6633f85408293fc7363f959b9b5c00b75341a20c892692e0863fff7e1

Observation 9fe6b26e-9b3f-413f-880b-cf076fce5627 · outbound

This paper cites 2024 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , url=

Reference 53

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source=arxiv_source observed=2026-08-03T11:54:19.658771Z digest=sha256:40516e7262e8870df25e2d8814bdac6714070c219119122bdaf05cfa368a29c8

Observation 8490e5a6-efec-4200-9b9c-6b77fd8b4f2b · outbound

This paper cites 2024 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , doi=

Reference 54

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source=arxiv_source observed=2026-08-03T11:54:19.768540Z digest=sha256:d272b07523fdeb0fdcecf5e2a356aa36726f2fa0d6ee173c9643d798b4e546a5

Observation ec380178-7336-48b2-b2b0-a99ee1226891 · outbound

This paper cites , booktitle=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding , booktitle=

Reference 55

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source=arxiv_source observed=2026-08-03T11:54:19.822413Z digest=sha256:6a258b6020b69ebdc3ca37ffafaeee9abdee17cd680df912925ad696f9efa1e0

Observation ea13f156-fe1a-42fa-a5ab-b8b3fec5e3d6 · outbound

This paper cites 2025 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , doi=

Reference 56

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source=arxiv_source observed=2026-08-03T11:54:19.880510Z digest=sha256:3623efcb86a2a76dc2a7cc0e32ec44cfc45ef7350201b7d31d566243106bb852

Observation ccc75343-87c4-4b25-b198-625431b2b9b1 · outbound

This paper cites and Yue, Summer and Xing, Chen , booktitle=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding and Yue, Summer and Xing, Chen , booktitle=

Reference 57

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source=arxiv_source observed=2026-08-03T11:54:20.006529Z digest=sha256:550238d2e446f055412eae2fc560636c6cb8a534f02ed8d201107b05c3aaf66f

Observation 11e4d667-1bda-4031-b82c-dffdd013b812 · outbound

This paper cites 2025 , publisher=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , publisher=

Reference 58

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source=arxiv_source observed=2026-08-03T11:54:20.045358Z digest=sha256:a16ad858fd3159b805ecc3d4c35514ead263c6d27457cf250022801e9c51bce1

Observation 1e18a762-7b4d-426c-9b8f-4260c74beae7 · outbound

This paper cites ACL Short Papers , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding ACL Short Papers , year=

Reference 59

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verified exact
doi, observed 2026-08-03T11:59:12.218601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-03T11:54:20.086287Z digest=sha256:c1d9f1cf94e663a9daf54de055c580c9513d45d554d1a907d39ed6fe9bc087a6

Observation 84a5a9e6-6b63-40d0-b986-1b213fa56d81 · outbound

This paper cites TACL , volume=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding TACL , volume=

Reference 60

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source=arxiv_source observed=2026-08-03T11:54:20.132395Z digest=sha256:098357cc5649ad2e6a7cada4a2e78b0f1e6ada596a1ccdf14d4468ef78840146

Observation 0ff98886-80a2-4e70-bc53-3359ec0e3565 · outbound

This paper cites 2025 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , doi=

Reference 61

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source=arxiv_source observed=2026-08-03T11:54:20.192447Z digest=sha256:e2ca699576ef603843e660294ab5d97a7d5a39da31c44763ba64a845d3965256

Observation 0c6f0438-6623-4b24-a9e8-8e7f29f87cf6 · outbound

This paper cites EMNLP Findings , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding EMNLP Findings , year=

Reference 62

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source=arxiv_source observed=2026-08-03T11:54:20.238557Z digest=sha256:0e437fc61dc635fc9639bf3a34f6fc4ab1c2faea3442d8b16743617926a401ba

Observation 3e1e7f3f-85ad-456b-afc7-a08bed963865 · outbound

This paper cites 2025 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , url=

Reference 63

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source=arxiv_source observed=2026-08-03T11:54:20.342561Z digest=sha256:56223b5d840489865fe8db35b2816ba6d5c14e1dbd2709d65b62c9d7d69738ec

Observation 0fb63212-b825-4aed-af41-f80ac3d69a1b · outbound

This paper cites One Battle After Another: Probing.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding One Battle After Another: Probing

Reference 64

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doi, observed 2026-08-03T11:59:11.909726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-03T11:54:20.448065Z digest=sha256:dbf8d76acd7c9e264b45003a5d823366be9b833920a31617aa14c7378422872b

Observation 2f64be0f-f0ac-4694-bf3c-e4213f1548a3 · outbound

This paper cites ACL , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding ACL , year=

Reference 65

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source=arxiv_source observed=2026-08-03T11:54:20.485039Z digest=sha256:dd91a0d386c78c2b6b79c182e1377aa3efa1ebe1d4974cc86f46583e2edf470f

Observation a17c039c-748a-46fc-b388-7252a5c1637d · outbound

This paper cites 2023 , eprint=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2023 , eprint=

Reference 66

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source=arxiv_source observed=2026-08-03T11:54:20.538257Z digest=sha256:3633fff77aad059c50845d093c631109dfa262134f57236e58da7c582ad10913

Observation dde7cb24-6ccc-4263-b316-b5e9b5f6586e · outbound

This paper cites 2024 , doi=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , doi=

Reference 67

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source=arxiv_source observed=2026-08-03T11:54:20.650070Z digest=sha256:601b0380e4649bf3cfc809242edb5ae44449172b56e67ec2fb3395b3370fada4

Observation fa650952-5d5a-4684-b682-9a9d4e91de11 · outbound

This paper cites Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge

Reference 68

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source=arxiv_source observed=2026-08-03T11:54:20.710057Z digest=sha256:2830b4c399f130b0c405ad131820cc114f10fad4ccc9752616ed306dee1afbfa

Observation 111450b6-8723-4fd4-8784-5e7c7c74343e · outbound

This paper cites 2024 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , pages=

Reference 69

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source=arxiv_source observed=2026-08-03T11:54:20.763870Z digest=sha256:06a6e55f1e61e9f060c92edd03973cee8da6de0f59bb073534188c394df44d36

Observation 44e57a8b-8d57-4ef3-8593-58be3d7b9d0c · outbound

This paper cites 2024 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , pages=

Reference 70

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source=arxiv_source observed=2026-08-03T11:54:20.871776Z digest=sha256:7ddc54e1b56ea526718deba5fa6aeb468d9317d17241ea6ec8d1c5369b3750b4

Observation 5018c1a1-57bb-48e3-aa00-867b84183756 · outbound

This paper cites 2025 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , pages=

Reference 71

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doi, observed 2026-08-03T11:59:11.494999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-03T11:54:20.981497Z digest=sha256:2891bdfa04bac6804791cd9123e0191e945b85289d54701f391d072bfaf82f23

Observation 520d4e1f-1fbe-43f6-ac24-ae0b9bf60f74 · outbound

This paper cites 2024 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , pages=

Reference 72

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source=arxiv_source observed=2026-08-03T11:54:21.036528Z digest=sha256:5ba6c33114d2095e109e058862027ccf0b7bc020f6bfcc13005ed5b2789cca91

Observation 49fd23ea-58a5-4393-958e-2a8ef63f2b9f · outbound

This paper cites NeurIPS , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding NeurIPS , year=

Reference 73

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source=arxiv_source observed=2026-08-03T11:54:21.099778Z digest=sha256:8762daf867f01a073c7ed460aa2727549fa5d24fe94bd7bcf3deb0f53bd487a9

Observation ddc43a79-eb40-46fb-acd0-552c57942b1f · outbound

This paper cites 2024 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , pages=

Reference 74

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source=arxiv_source observed=2026-08-03T11:54:21.251825Z digest=sha256:0f834c7653417ac396edaa8fccfc3ebbf3e722ccc9f3d575941428940e8ed080

Observation a920d421-8dc4-4892-a761-94487f9b8672 · outbound

This paper cites 2024 , pages=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , pages=

Reference 75

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source=arxiv_source observed=2026-08-03T11:54:21.319604Z digest=sha256:57e5dc55a7c6845d5fcc42c7dbb6ae83692b06c4a7cb89b2de1c94b0ec127224

Observation 3f7d2321-4a16-4707-81db-30f55d960c9a · outbound

This paper cites 2025 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , url=

Reference 76

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source=arxiv_source observed=2026-08-03T11:54:21.353611Z digest=sha256:8c566911034222710073dfa9da1e9e145237eef8e05c5adfa1b27c5800d0544e

Observation d34b4f04-1c03-431a-8fb6-c59f52c4fdb4 · outbound

This paper cites ICML , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding ICML , year=

Reference 77

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source=arxiv_source observed=2026-08-03T11:54:21.409490Z digest=sha256:4a4a24bf623decd0396cc452967777b3f46e8246226d27828ce298884a6f24ef

Observation 03c31d39-a66f-49dd-81d9-318030a90c71 · outbound

This paper cites , booktitle=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding , booktitle=

Reference 78

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no resolver link, observed 2026-08-03T11:54:21.525763Z

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source=arxiv_source observed=2026-08-03T11:54:21.525763Z digest=sha256:74a810a7320b1b9d194bdc53d386158569ccd93900d383b4e8370dacfbca18c0

Observation ba903d10-a02c-4f8f-94c5-b909c9858ecf · outbound

This paper cites ICLR , year=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding ICLR , year=

Reference 79

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source=arxiv_source observed=2026-08-03T11:54:21.565721Z digest=sha256:ae63e1a9f1f48c2ff010f167625d5a5a6ee0caaf06079054a849e1dd9c442a2a

Observation a79af1e1-4b35-4cea-8893-137854931432 · outbound

This paper cites 2024 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , url=

Reference 80

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source=arxiv_source observed=2026-08-03T11:54:21.635669Z digest=sha256:b184ee3a784722f877d72ef91275513d3f4438854d1217a836ed3de82083d221

Observation b2f778f6-c09c-4024-8d6c-daeaee36b10c · outbound

This paper cites 2024 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2024 , url=

Reference 81

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no resolver link, observed 2026-08-03T11:54:21.790097Z

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source=arxiv_source observed=2026-08-03T11:54:21.790097Z digest=sha256:c97ab6023a411d86e3e97ae9c6af9ec206ca3dc9bc3a598dd4ce91f4b013f505

Observation 25d9b991-0926-405b-9e14-28231ba76393 · outbound

This paper cites MemoryBank: Enhancing Large Language Models with Long-Term Memory.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding MemoryBank: Enhancing Large Language Models with Long-Term Memory

Reference 82

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source=arxiv_source observed=2026-08-03T11:54:21.890923Z digest=sha256:745f3fff358e30c33cb9af9897dbb6989702a3f3274689a0863988b3a7362890

Observation 797a342e-00e3-498f-8edb-8c80e1f6b7c7 · outbound

This paper cites MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions

Reference 83

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source=arxiv_source observed=2026-08-03T11:54:21.954324Z digest=sha256:a76716eb5282249f958a0c889a6cdd97a7a8e9d5efcc45c8fe7fe37dc698ac10

Observation 8f1184d0-7747-431d-9ba4-9b1405d0be97 · outbound

This paper cites LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks

Reference 84

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source=arxiv_source observed=2026-08-03T11:54:22.062287Z digest=sha256:d93bb854b7765d8aab7b01e423462014f0eead8c3964a949d9402d517ae5b5ab

Observation 6f4a9a03-ba82-4baf-8216-f299468682ce · outbound

This paper cites 2025 , url=.

Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding 2025 , url=

Reference 85

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source=arxiv_source observed=2026-08-03T11:54:22.116161Z digest=sha256:34184bbf407cf9df94694c64f79682832495a10498b3c211ba1921fd2c97a002

Pith citing papers

No inbound Pith citation observations are available.