Pith. sign in

Paper Citation Record · LEDGER

Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2406.11695.

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

pith.paper-citation-record.v1
2406.11695 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:25:14.752902Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9348ef59-3d4e-4451-9839-78bda0ce0bc7 · inbound

LLM-AutoDiff: Auto-Differentiate Any LLM Workflow cites this paper.

LLM-AutoDiff: Auto-Differentiate Any LLM Workflow Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T11:33:24.636555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T11:33:24.636555Z digest=sha256:42c5bcfc22940e01c60a2a31dc19c7a4bf705030298171e7c0a7c0325887fbca

Observation 07fb4be5-6b6e-4915-87ed-7552e02ba394 · inbound

Querying Databases with Function Calling cites this paper.

Querying Databases with Function Calling Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T15:25:14.752902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:25:14.752902Z digest=sha256:f87b50783acf0f5aeaa8c23c7a4c5bbdb877cb35e12d9cd6fd251e9f5d5d2a18

Observation 00dd4f4f-c7da-45ec-b445-6fd9a169abbf · inbound

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation cites this paper.

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-09T19:31:49.701468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:31:49.701468Z digest=sha256:0d1a6eb4793b3be0f660b265d87c9e829bf86dc76b2388ce157087dad9b4b67b

Observation 5f5dde57-31f6-4e41-bdf7-e4b1d6d36c36 · inbound

Meta-Prompt Optimization for LLM-Based Sequential Decision Making cites this paper.

Meta-Prompt Optimization for LLM-Based Sequential Decision Making Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T18:00:22.186149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:00:22.186149Z digest=sha256:425f4a6da93511970430c27ef8ff14da4e68ae03605693d0fc12257b603ce16e

Observation dcdd57e7-914b-4bf3-9102-149a52db2a10 · inbound

Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning cites this paper.

Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-08T11:03:44.643296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:03:44.643296Z digest=sha256:cd9ef2747e1d74670f813da8b7b99d8276c5531eea81bb5768048549e94f4c28

Observation bcaa0cc7-742a-4480-8725-d4d226cacc5a · inbound

Improved Representation Steering for Language Models cites this paper.

Improved Representation Steering for Language Models Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T13:51:30.997743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:51:30.997743Z digest=sha256:ae95ea7fcf784e290543d3f301f3da5d7c8ba0ba8febe0b082776285b4e2d409

Observation 78a10724-4731-4b8d-80bc-c64983098631 · inbound

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy cites this paper.

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T12:53:42.259489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:53:42.259489Z digest=sha256:4aac286c736f00bedb51ecfe18a88054a10ebbad5d495261f0e0e66ce251f764

Observation 3bed5237-b67d-4a41-a8b9-a3c9fd1cd29d · inbound

Transforming Expert Knowledge into Scalable Ontology via Large Language Models cites this paper.

Transforming Expert Knowledge into Scalable Ontology via Large Language Models Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T05:21:03.090383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:21:03.090383Z digest=sha256:735feee72e2d5513b0a7083c471c3214d4b899dcd5083784b01f8c7ff296fd8b

Observation c76ffacd-76cd-45b6-8533-4b312a2aa0ae · inbound

Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge cites this paper.

Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:36.330887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:36.330887Z digest=sha256:602d3a72168e7e0ff2c8fcf236d6422eb03e5fcf035fa6a4ce48fd85b4dced71

Observation 9671d293-2436-4a9e-a593-f982f9284599 · inbound

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy cites this paper.

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T20:09:18.293773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:09:18.293773Z digest=sha256:eafebef0f164af9336eab93866b90fbe8aa940e8a80cd2612f6ee0487fca9252

Observation 7795f177-c695-42ab-b793-3fe0f15abb32 · inbound

Maestro: Joint Graph & Config Optimization for Reliable AI Agents cites this paper.

Maestro: Joint Graph & Config Optimization for Reliable AI Agents Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T05:59:49.956160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:59:49.956160Z digest=sha256:c157671a6727291593b70786038f1e49e16f52b05db93a5cddf6c1d689b6ba12

Observation 7fa8fa9b-2198-46e9-b6dc-f10946c524c7 · inbound

FEM-Bench: A Structured Scientific Reasoning Benchmark for Evaluating Code-Generating LLMs cites this paper.

FEM-Bench: A Structured Scientific Reasoning Benchmark for Evaluating Code-Generating LLMs Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T14:21:29.224977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:21:29.224977Z digest=sha256:0f57045bf3e4e6e487095a09118699e93a21a37bb301c01fb1d8ee2c9e5c9702

Observation 1649c6f5-32f5-4919-b0b9-ce8f89cd8750 · inbound

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions cites this paper.

Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-02T23:04:33.688502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:04:33.688502Z digest=sha256:7e23f81ac48672a3f2a39f3cfaf01d69286d36b4e71696ca1dc4f18a1d85953e

Observation 4d44544c-24f4-4d04-b2da-e2976d096b0e · inbound

EditFlow: Benchmarking and Optimizing Code Edit Recommendation Systems via Reconstruction of Developer Flows cites this paper.

EditFlow: Benchmarking and Optimizing Code Edit Recommendation Systems via Reconstruction of Developer Flows Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:46:33.068066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T19:43:47.791634Z digest=sha256:bdb32477bacdc7f8102d5a235856c9674f4ce1386f0ca57d1d703f591a5a2e80

Observation 956732c3-6279-43b7-b030-b578513e2973 · inbound

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks cites this paper.

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T19:22:25.394087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T19:22:25.394087Z digest=sha256:3b3660c462e5be2779c76b61b16a88b0d70268ce9fcee1404b3aefe08518093d

Observation 1b55ba21-b018-475a-9c95-c3a45ad72ded · inbound

DetPO: In-Context Learning with Multi-Modal LLMs for Few-Shot Object Detection cites this paper.

DetPO: In-Context Learning with Multi-Modal LLMs for Few-Shot Object Detection Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 41

Resolution
unresolved
no resolver link, observed 2026-07-13T19:38:38.452093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T19:38:38.452093Z digest=sha256:58096890c944a37a8f68cbcc84e6610e6c693871f6ce347cc313067f25adb113

Observation 17c590fc-4768-46f5-97d0-81693233e15a · inbound

Automated Instruction Revision (AIR): A Structured Comparison of Task Adaptation Strategies for LLM cites this paper.

Automated Instruction Revision (AIR): A Structured Comparison of Task Adaptation Strategies for LLM Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T06:46:29.492893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T17:27:37.081594Z digest=sha256:615753f142d5aeef1805e4a8bb94df828398ea76eb24f3ad971c72a90947ddda

Observation 4a070fa4-b20b-4fbe-9381-9d0cbe2e1a92 · inbound

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients cites this paper.

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:01:24.438590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-07T13:22:30.744798Z digest=sha256:1858be0e69c555bbf53055ace8c5a0e744db0028c1925ce922ebb22e815d214b

Observation eac21947-ce6e-4326-9170-f13f1fcce05a · inbound

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients cites this paper.

FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 525

Resolution
unresolved
no resolver link, observed 2026-08-02T15:20:21.465700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:20:21.465700Z digest=sha256:c8af4bd55d17674a9f0655af072505890694160fea62714249f7999640d93d53

Observation ed987d94-b357-4afb-a0c2-0ffa85cadeca · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:07:18.516637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-13T05:00:31.452781Z digest=sha256:19f660c8641ed638e2661c24a8c392355a1a660bfe25017760e2da0462635c46

Observation cc8dadb1-c828-497e-b23d-c512ad547ed1 · inbound

Learning, Fast and Slow: Towards LLMs That Adapt Continually cites this paper.

Learning, Fast and Slow: Towards LLMs That Adapt Continually Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:19:45.782446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T05:19:05.368681Z digest=sha256:908072dbd8c52fc7c1042c35767568ff45953f64659765601e37167caace6e2e

Observation 428c4ac4-ad61-4d55-9849-92f41be5c158 · inbound

Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering cites this paper.

Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:08:54.436058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-20T19:05:58.638818Z digest=sha256:aaed151f59aab8bd6eb3d33e9bb3c3bcf951405e181e974a2a266852af099314

Observation bb6c8b2a-13fa-4a2c-a465-adde1a1c4bdc · inbound

optimize_anything: A Universal API for Optimizing any Text Parameter cites this paper.

optimize_anything: A Universal API for Optimizing any Text Parameter Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-20T05:43:23.258234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-20T05:43:07.394497Z digest=sha256:bdd6d638c8420d8cf402786e4b2aeee1fe0c8a28272e71092a58f64b4ca67eec

Observation 7e14c2bb-3823-4d4e-8e91-e714d77aea3c · inbound

LLMs Are Already Good Tutors: Training-Free Prompt Optimization for Pedagogical Math Tutoring cites this paper.

LLMs Are Already Good Tutors: Training-Free Prompt Optimization for Pedagogical Math Tutoring Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T17:53:47.043289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-29T17:50:46.072234Z digest=sha256:5c1939b1c2b0103455f807c148aa93b0ac2b3e03d675ced7e447cdee3084053c

Observation 8dec919b-ec1e-47f8-810e-1f6bbfce5bd5 · inbound

Evolving and Detecting Multi-Turn Deception using Geometric Signatures cites this paper.

Evolving and Detecting Multi-Turn Deception using Geometric Signatures Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T15:23:32.665512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-29T15:17:58.804973Z digest=sha256:04e5e39521a123d17790eaed716e501fc4c6ed051faf49b994dd5e3f58076da1

Observation 1b841605-6f79-435a-97a0-a98481ecacef · inbound

Trace2Policy: From Expert Behavior Traces to Self-Evolving Decision Agents cites this paper.

Trace2Policy: From Expert Behavior Traces to Self-Evolving Decision Agents Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T05:27:39.675777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-27T13:19:10.714343Z digest=sha256:ec383f8608345dcc02282a1ffe82223177f64070ddf8db8243740bd8830a28c5

Observation a378eb4a-b571-4d0e-85fb-b96a6062095a · inbound

IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction cites this paper.

IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:29:02.548224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-26T22:14:21.463271Z digest=sha256:14221cfeb8596b2f4d801c37a738ba4ef4e13faa3ceb6b4c720fb879d4b8c4b6

Observation 3487d8fd-465d-4baa-9a8d-0053bb5e211f · inbound

IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction cites this paper.

IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-12T13:33:24.392944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:33:24.392944Z digest=sha256:1a05d4bc7a0698bddbda38b342a3b4dd8b834ad2f359aeb088443d0428137428

Observation 30ce260b-e0ef-4d50-8214-feb17c8fac99 · inbound

Contrastive Reflection for Iterative Prompt Optimization cites this paper.

Contrastive Reflection for Iterative Prompt Optimization Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T12:25:44.298920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-01T02:02:22.841488Z digest=sha256:64f9f21beea97f2a0cbfbc6df993d34f480404e0efca5584afdd845af441f762

Observation 1d5d6830-e951-4b4f-b5bb-8e1d115ef81e · inbound

Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.0 cites this paper.

Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.0 Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T03:07:00.083970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:07:00.083970Z digest=sha256:184a7883e0cb7c0121128c6f05457993f1c6a0735818b8da7ea77e6cb927ad46

Observation e44b16c4-5643-4fb6-9db9-d02d104a17c5 · inbound

MemoHarness: Agent Harnesses That Learn from Experience cites this paper.

MemoHarness: Agent Harnesses That Learn from Experience Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-02T05:43:00.437816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T05:43:00.437816Z digest=sha256:9e0e5b500e9ba84b9cf7a374beadb998c8aa8fbf83fdedd11e6294ae539c1117

Observation 705cc7a3-8874-4d61-a8cf-bd9c34583612 · inbound

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories cites this paper.

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T10:10:32.422182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:10:32.422182Z digest=sha256:116177ff0ad2478650070dd3d8c396db9c68a815fe25b9cca420b1a89378ddfb

Observation e4a1719a-3cac-4952-b079-947b6add83a4 · inbound

On the missing benchmarks layer and a potential solution cites this paper.

On the missing benchmarks layer and a potential solution Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T04:17:31.840402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:17:31.840402Z digest=sha256:14ca63a7e8c2058c1182015ca19d2ed75dac1c16533effef6933260b640519fa