Paper Citation Record · LEDGER

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants

As of 13 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 4 inbound Pith citation observations for arXiv:2505.19797.

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

pith.paper-citation-record.v1
2505.19797 v3

Coverage vector

measured 81 of 81 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:12:41.299745Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T06:50:32.988192Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:39:42.725608Z

Reference resolution

81 of 81 outbound references displayed

verified exact1
verified fuzzy15
unresolved64
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40727cc4-89c2-4352-ba28-3d7a1cebae19 · outbound

This paper cites Ultramedical: Building specialized generalists in biomedicine.Advances in Neural Information Processing Systems, 37:26045–26081, 2024.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Ultramedical: Building specialized generalists in biomedicine.Advances in Neural Information Processing Systems, 37:26045–26081, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.199371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9b0f1bb-8b26-4140-a282-4a479c9cc5d9 · outbound

This paper cites Process Reinforcement through Implicit Rewards.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Process Reinforcement through Implicit Rewards

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.288204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe54bbbc-efbd-4f4d-9c5f-d94ca7681837 · outbound

This paper cites Building community–centered ai collaborations.Stanford Social Innovation Review, 2025.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Building community–centered ai collaborations.Stanford Social Innovation Review, 2025

Reference 5

Resolution: verified exact; doi, observed 2026-08-07T14:12:41.577912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0cf29427-7c22-4eb8-b345-eb9916c809d6 · outbound

This paper cites Green ai.Communications of the ACM, 63(12):54–63, 2020.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Green ai.Communications of the ACM, 63(12):54–63, 2020

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.412441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48d278ac-5ad7-4ee5-b5e1-727f72c623f6 · outbound

This paper cites Llm-blender: Ensembling large language models with pairwise ranking and generative fusion.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Llm-blender: Ensembling large language models with pairwise ranking and generative fusion

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.443105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dd2b6a1-42ad-4f6a-af2d-2137969ed899 · outbound

This paper cites Routerdc: Query-based router by dual contrastive learning for assembling large language models.Advances in Neural Information Processing Systems, 37:66305–66328, 2024.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Routerdc: Query-based router by dual contrastive learning for assembling large language models.Advances in Neural Information Processing Systems, 37:66305–66328, 2024

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.508393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a043797a-6c98-4d01-8200-ccf8c49467de · outbound

This paper cites EmbedLLM: Learning Compact Representations of Large Language Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants EmbedLLM: Learning Compact Representations of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.610647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4356e91a-2922-4bb4-8c5a-be5159899cfa · outbound

This paper cites Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.689491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36bff3ba-2059-4750-a495-602f6fbc05be · outbound

This paper cites Mixture-of-Agents Enhances Large Language Model Capabilities.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Mixture-of-Agents Enhances Large Language Model Capabilities

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.756291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 033928a1-74e0-4388-a982-e9f5a9e1f9d1 · outbound

This paper cites SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.827163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd312a38-b50a-40bb-8035-fc42a18c168a · outbound

This paper cites Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.899732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 159b6e42-542c-4c58-a907-29649658a76b · outbound

This paper cites Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:35.977713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6313b18-acce-4e0e-9b9c-b991859a7055 · outbound

This paper cites Least squares quantization in pcm.IEEE transactions on information theory, 28 (2):129–137, 1982.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Least squares quantization in pcm.IEEE transactions on information theory, 28 (2):129–137, 1982

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:47.201132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fc4a2997-feea-4b8e-bb4e-3a486bff15bd · outbound

This paper cites Some methods for classification and analysis of multivariate observations.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Some methods for classification and analysis of multivariate observations

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.141208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9022ab54-7396-41a4-a303-2c11af058e1b · outbound

This paper cites Hierarchical grouping to optimize an objective function.Journal of the American statistical association, 58(301):236–244, 1963.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Hierarchical grouping to optimize an objective function.Journal of the American statistical association, 58(301):236–244, 1963

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.213517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0270721e-26a9-4d7f-9a86-bd16f0c290b7 · outbound

This paper cites Maximum likelihood from incomplete data via the em algorithm.Journal of the royal statistical society: series B (methodological), 39 (1):1–22, 1977.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Maximum likelihood from incomplete data via the em algorithm.Journal of the royal statistical society: series B (methodological), 39 (1):1–22, 1977

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.287144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c044fd9-00b8-4d4e-8096-cfd7c8375508 · outbound

This paper cites A tutorial on spectral clustering.Statistics and computing, 17:395–416, 2007.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants A tutorial on spectral clustering.Statistics and computing, 17:395–416, 2007

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:46.966106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c8cd042-06b9-411e-8d19-50486b71faf9 · outbound

This paper cites Birch: an efficient data clustering method for very large databases.ACM sigmod record, 25(2):103–114, 1996.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Birch: an efficient data clustering method for very large databases.ACM sigmod record, 25(2):103–114, 1996

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:46.788424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c6612984-5807-44ed-96e7-88ba62a2fd86 · outbound

This paper cites Do we truly need so many samples? multi-llm repeated sampling efficiently scales test-time compute, 2025.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Do we truly need so many samples? multi-llm repeated sampling efficiently scales test-time compute, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.558086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a3ecc51-4152-4ff9-adc9-aaf5dc8a5fc6 · outbound

This paper cites Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.638918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f793d956-28ae-4384-b783-ac7a5568aca9 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.726487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2768a49b-7467-44b5-8d34-d19c554ca877 · outbound

This paper cites Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.790347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0a64fdc-e1cd-47f3-86ee-df9b3d89cd9f · outbound

This paper cites Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.902960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62982040-85bf-419d-847c-47830da565b7 · outbound

This paper cites ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:36.983847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40c5e453-f89c-4a70-8ff9-57580ddbeb7c · outbound

This paper cites Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.078175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20b942bf-3972-45af-b197-b88299524071 · outbound

This paper cites Frugalgpt: How to use large language models while reducing cost and improving performance.Transactions on Machine Learning Research, 2023.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Frugalgpt: How to use large language models while reducing cost and improving performance.Transactions on Machine Learning Research, 2023

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:46.588515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e87960c1-73a9-4cdf-bfd5-aa3e5c3119c2 · outbound

This paper cites Large language model routing with benchmark datasets.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Large language model routing with benchmark datasets

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:46.407053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5afe43e8-d1fc-454d-98f5-df9bec08f80f · outbound

This paper cites Routellm: Learning to route llms from preference data.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Routellm: Learning to route llms from preference data

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.325106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 149610e5-1443-4cbc-b741-be44f72de33a · outbound

This paper cites Graphrouter: A graph-based router for LLM selections.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Graphrouter: A graph-based router for LLM selections

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:46.190467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6ce721fc-d760-4a8e-a021-a764cbf6ceda · outbound

This paper cites Learning to decode collaboratively with multiple language models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Learning to decode collaboratively with multiple language models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:45.976139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2deb8c0a-17a0-472d-bf21-777bba6b2774 · outbound

This paper cites RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.520825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82614c28-d3c6-4df2-8f2f-f7f48ecf8ee9 · outbound

This paper cites Routing to the expert: Efficient reward-guided ensemble of large language models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Routing to the expert: Efficient reward-guided ensemble of large language models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.591132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4beac04-7931-4f90-a594-d923ea16e58d · outbound

This paper cites Routerbench: A benchmark for multi-llm routing system.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Routerbench: A benchmark for multi-llm routing system

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:45.733567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4f419691-4d86-4032-a51f-5f9d6a45859a · outbound

This paper cites Universal Model Routing for Efficient LLM Inference.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Universal Model Routing for Efficient LLM Inference

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.738204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 490677ab-20b0-4e18-a9ea-44df0d9fd852 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.837398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9bc7f2f-f6d1-45f8-afdb-53c02e9316b8 · outbound

This paper cites Let's Verify Step by Step.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Let's Verify Step by Step

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.898335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef7ceb3c-c176-4901-a189-8a16f228fc3b · outbound

This paper cites Are Your LLMs Capable of Stable Reasoning?.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Are Your LLMs Capable of Stable Reasoning?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:37.976334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53910b3e-2c36-42ea-8cff-6f68fda8d9bf · outbound

This paper cites Program Synthesis with Large Language Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Program Synthesis with Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.036261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70cd960c-cb1f-4e34-82fc-91a97f9e2cac · outbound

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The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.099130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2eabbc8-d7e9-4bd3-bdb6-451db023e848 · outbound

This paper cites KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.179668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07a88a96-8c18-4647-a1da-a500212b9a05 · outbound

This paper cites On Memorization of Large Language Models in Logical Reasoning.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants On Memorization of Large Language Models in Logical Reasoning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.271159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2745be6a-53dd-4298-b35e-dc56e3e358b6 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.361436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f57aa088-cec6-4ab9-95c2-61a5dce44f8f · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.422421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 920bf44d-0e85-4ff9-952e-45a6dd2a5aac · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.482386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 612a9233-f35e-4bd7-8785-a5f304bec58c · outbound

This paper cites an unresolved cited work.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.523935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f41818bb-464d-4d8f-a880-7b61580b2f65 · outbound

This paper cites Finqa: A dataset of numerical reasoning over financial data.Proceedings of EMNLP 2021, 2021.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Finqa: A dataset of numerical reasoning over financial data.Proceedings of EMNLP 2021, 2021

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:45.477542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4544dd5c-189a-450c-b1a8-bb4763c8478a · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.614600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea2d28da-679f-4e7c-bebd-0a23235ac6fa · outbound

This paper cites Ternary twitter sentiment classification with distant supervision and sentiment-specific word embeddings.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Ternary twitter sentiment classification with distant supervision and sentiment-specific word embeddings

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:45.228304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 85309405-8326-4388-82fb-9ed6d554e342 · outbound

This paper cites MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.697653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2593c843-c04f-47c9-9431-139f71010cd0 · outbound

This paper cites MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.725841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f77e8a2-36db-4082-a7fd-34984ab7f5df · outbound

This paper cites StudentEval: A Benchmark of Student-Written Prompts for Large Language Models of Code.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants StudentEval: A Benchmark of Student-Written Prompts for Large Language Models of Code

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.803262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8062eb0-ec71-46b9-86e6-508b5a4ab192 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Winogrande: An adversarial winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.874929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2db3300c-2856-48d1-b79a-fb58362a08dd · outbound

This paper cites Nimz at semeval-2024 task 9: Evaluating methods in solving brainteasers defying commonsense.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Nimz at semeval-2024 task 9: Evaluating methods in solving brainteasers defying commonsense

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:45.041452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 894b9fbb-2a08-4761-b00a-a40a4a9a8c2e · outbound

This paper cites DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:38.970143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38fec683-be4a-4777-9b79-953f7bd42844 · outbound

This paper cites Bge m3- embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation, 2024.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Bge m3- embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation, 2024

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.008945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 111b3849-ca99-4516-b251-2d10c1d17ce6 · outbound

This paper cites New embedding models and api updates.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants New embedding models and api updates

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:44.745757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1d7a16f0-83ad-4c4e-b002-02179f645ebd · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.168293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7fb2793-ca45-4ede-aa2f-c75379575b0e · outbound

This paper cites Ties-merging: Resolving interference when merging models.Advances in Neural Information Processing Systems, 36:7093–7115, 2023.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Ties-merging: Resolving interference when merging models.Advances in Neural Information Processing Systems, 36:7093–7115, 2023

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.247271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 189fe4db-49c6-4dc7-9333-a9d3bd3d86ce · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.307753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d985e190-dc36-4abe-8120-2686116cfdd8 · outbound

This paper cites Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.402491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6bc66f5-0414-4541-8f54-c0fc36e37fb7 · outbound

This paper cites Lorahub: Efficient cross-task generalization via dynamic lora composition.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Lorahub: Efficient cross-task generalization via dynamic lora composition

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:44.464945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 015ce0c8-398a-4c6a-a1f1-f48f609eb62b · outbound

This paper cites Nature-Inspired Population-Based Evolution of Large Language Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Nature-Inspired Population-Based Evolution of Large Language Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.569027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 978c092a-bc3f-4e6c-b9f4-17a4f02b0365 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Lora: Low-rank adaptation of large language models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.670308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 999710fb-ac4a-43c4-809a-3567aaa182c8 · outbound

This paper cites What Matters for Model Merging at Scale?.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants What Matters for Model Merging at Scale?

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.743785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e259725-7033-4ead-8325-985b6928e023 · outbound

This paper cites Fin-r1: A large language model for financial reasoning through reinforcement learning, 2025.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Fin-r1: A large language model for financial reasoning through reinforcement learning, 2025

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.856359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50bfa14f-9782-4318-8e3b-fc680987f7f2 · outbound

This paper cites Qwen2.5 Technical Report.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Qwen2.5 Technical Report

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.899006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7296880a-8306-4bc1-b1ca-5bd6d2538855 · outbound

This paper cites Qwen2.5-Coder Technical Report.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Qwen2.5-Coder Technical Report

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:39.958227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8af64a82-9d0a-408b-98df-7c32ff5398db · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.000511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38e5ed20-0135-4b1e-9e5d-fb91d8e09c36 · outbound

This paper cites The Llama 3 Herd of Models.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants The Llama 3 Herd of Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.038918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fbc5037-3051-4a57-867f-1c8c4dd08c6b · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Gemma 2: Improving Open Language Models at a Practical Size

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.105859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3445760c-ef17-4cfb-adb9-1cb3d95ecef8 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.191933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4174455-f16b-42bf-bbe9-7de0ea5d7188 · outbound

This paper cites Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.285327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56b07c24-4a35-4848-a891-5caf43577037 · outbound

This paper cites The falcon 3 family of open models, December 2024.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants The falcon 3 family of open models, December 2024

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:44.288792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c04829b6-9024-4e2a-bcd3-b332b97e9525 · outbound

This paper cites Mistral 7B.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Mistral 7B

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.531605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 906f2532-a3ce-40eb-9603-cb6ba7dbaac1 · outbound

This paper cites 2 OLMo 2 Furious.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants 2 OLMo 2 Furious

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.714477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a10e079-fc74-4353-a638-866bb3190d19 · outbound

This paper cites Internlm2 technical report, 2024.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Internlm2 technical report, 2024

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:12:44.133919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da39e628-124e-47b7-9c16-7071d0169793 · outbound

This paper cites Hermes 3 Technical Report.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Hermes 3 Technical Report

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:40.950374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01e80dcf-b99b-43bb-8f25-cf4e6bd3c6f0 · outbound

This paper cites MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:41.049270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd9d1863-7b48-4059-81b4-9e52c7c34be1 · outbound

This paper cites Llama-nemotron: Efficient reasoning models, 2025.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Llama-nemotron: Efficient reasoning models, 2025

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:41.131563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2716ba44-d95d-4d56-8e4a-84be6aff1f65 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T14:12:41.220423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdafd419-bc71-4fd4-9305-ce676d11f6e5 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants Yi: Open Foundation Models by 01.AI

Reference 83

Resolution: malformed identifier; no resolver link, observed 2026-08-07T14:12:41.299745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation e1f9e97e-8724-483f-ad4c-1ff51b64284f · inbound

MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings cites this paper.

MTRouter: Cost-Aware Multi-Turn LLM Routing with History-Model Joint Embeddings The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:16:12.413947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7166bdaa-3800-4c2a-a3ac-431fe9f75fc3 · inbound

DLLG: Dynamic Logit-Level Gating of LLM Experts cites this paper.

DLLG: Dynamic Logit-Level Gating of LLM Experts The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:36:45.096717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d2ca031b-75d6-4871-913e-9fc17fb9e894 · inbound

RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing cites this paper.

RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T00:19:13.477308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3c7cf5fd-d7bc-4fa8-9cb9-14b28404fdea · inbound

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents cites this paper.

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants

Reference 138

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:39:42.727124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.