Paper Citation Record · LEDGER

Predicting Emergent Capabilities by Finetuning

As of 19 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2411.16035.

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

pith.paper-citation-record.v1
2411.16035 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:41:46.254216Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:21:06.816340Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T17:21:06.986406Z

Reference resolution

62 of 62 outbound references displayed

verified exact1
verified fuzzy11
unresolved50
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34b427c7-d979-44dd-9e22-84af62f7b809 · outbound

This paper cites Many-Shot In-Context Learning.

Predicting Emergent Capabilities by Finetuning Many-Shot In-Context Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:45.965971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7867831-24b2-4bcc-b60b-1bab32606976 · outbound

This paper cites Scaling laws for generative mixed-modal language models, 2023.

Predicting Emergent Capabilities by Finetuning Scaling laws for generative mixed-modal language models, 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.160971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0cf24f91-bdd7-489f-914a-6cd8eac2dcb7 · outbound

This paper cites Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, et al.

Predicting Emergent Capabilities by Finetuning Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, et al

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.145463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8bdcc17c-1756-49fd-b3e0-98dcec4f223b · outbound

This paper cites Foundational Challenges in Assuring Alignment and Safety of Large Language Models.

Predicting Emergent Capabilities by Finetuning Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:45.982526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c1a7b28-08f5-4adb-9af4-79dac01906ae · outbound

This paper cites Zoology: Measuring and Improving Recall in Efficient Language Models.

Predicting Emergent Capabilities by Finetuning Zoology: Measuring and Improving Recall in Efficient Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:45.987890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d775fd2b-0baa-48c2-86f0-40f2194cf5aa · outbound

This paper cites Program Synthesis with Large Language Models.

Predicting Emergent Capabilities by Finetuning Program Synthesis with Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:45.992980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bdaeabc-85fb-496a-92b0-d2c47d0da5cc · outbound

This paper cites Emergent abilities and grokking: Fundamental, mirage, or both?, 2023.

Predicting Emergent Capabilities by Finetuning Emergent abilities and grokking: Fundamental, mirage, or both?, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.129582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c769af3d-4170-451c-938c-962f99453c2f · outbound

This paper cites Managing extreme AI risks amid rapid progress.

Predicting Emergent Capabilities by Finetuning Managing extreme AI risks amid rapid progress

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.003072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f125af7e-c2cb-4f1d-a55a-23303004c79e · outbound

This paper cites Does your data spark joy? Performance gains from domain upsampling at the end of training.

Predicting Emergent Capabilities by Finetuning Does your data spark joy? Performance gains from domain upsampling at the end of training

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.008379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 108a6f13-21b5-4d0d-a389-5b93dca50e05 · outbound

This paper cites JAX : composable transformations of P ython+ N um P y programs, 2018.

Predicting Emergent Capabilities by Finetuning JAX : composable transformations of P ython+ N um P y programs, 2018

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.014855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3246946a-4d6d-493d-a462-4de00aea052b · outbound

This paper cites Broken neural scaling laws, 2023.

Predicting Emergent Capabilities by Finetuning Broken neural scaling laws, 2023

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.104718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a2deb85d-13fb-46ca-9493-253dedd131f1 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Predicting Emergent Capabilities by Finetuning Evaluating Large Language Models Trained on Code

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.023929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc6ab49d-c021-4f46-b672-4f904ddb03e4 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Predicting Emergent Capabilities by Finetuning Training Verifiers to Solve Math Word Problems

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.028820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0649c6c-a796-496e-ad53-cd3b02d4502e · outbound

This paper cites Redpajama-data: An open source recipe to reproduce llama training dataset, 2023.

Predicting Emergent Capabilities by Finetuning Redpajama-data: An open source recipe to reproduce llama training dataset, 2023

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.090024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3a57637b-bf38-4e30-8a05-0ea8283a7b73 · outbound

This paper cites Understanding Emergent Abilities of Language Models from the Loss Perspective.

Predicting Emergent Capabilities by Finetuning Understanding Emergent Abilities of Language Models from the Loss Perspective

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.037754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 811e3b5e-fe73-40a7-a20b-28a7d7ca4a2f · outbound

This paper cites Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, and Ludwig Schmidt.

Predicting Emergent Capabilities by Finetuning Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, and Ludwig Schmidt

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.074811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe536083-937f-4ded-b8cc-a6848bdce38a · outbound

This paper cites Openllama: An open reproduction of llama, May 2023.

Predicting Emergent Capabilities by Finetuning Openllama: An open reproduction of llama, May 2023

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.045718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d25f746d-457c-4b9c-8190-5f986b7df5df · outbound

This paper cites Scalax: scaling utilities for jax, 2024.

Predicting Emergent Capabilities by Finetuning Scalax: scaling utilities for jax, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:47.049617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8d26cf8f-c2fa-4613-9b34-3ef6a28cb268 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Predicting Emergent Capabilities by Finetuning Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.053646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 135e0a4b-9270-44ee-99d1-482505704b16 · outbound

This paper cites The False Promise of Imitating Proprietary LLMs.

Predicting Emergent Capabilities by Finetuning The False Promise of Imitating Proprietary LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.057754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8a7c8c4-cc0d-46b6-a9d1-17a1c4f0103d · outbound

This paper cites Measuring massive multitask language understanding, 2021.

Predicting Emergent Capabilities by Finetuning Measuring massive multitask language understanding, 2021

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.062341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6137db7a-3b60-49da-adca-7e36a34382d0 · outbound

This paper cites An Overview of Catastrophic AI Risks.

Predicting Emergent Capabilities by Finetuning An Overview of Catastrophic AI Risks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.066786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02daedf1-52a2-420b-9b5a-1b4d56894c78 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Predicting Emergent Capabilities by Finetuning Scaling Laws for Autoregressive Generative Modeling

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.071559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f1bcd97-1a3b-41a9-bebd-9ada0aab95e0 · outbound

This paper cites Scaling Laws for Transfer.

Predicting Emergent Capabilities by Finetuning Scaling Laws for Transfer

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.076596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a264839-d387-4dde-a2d1-29cef7ffbb1f · outbound

This paper cites The no-u-turn sampler: adaptively setting path lengths in hamiltonian monte carlo.

Predicting Emergent Capabilities by Finetuning The no-u-turn sampler: adaptively setting path lengths in hamiltonian monte carlo

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.081425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca2b7058-a325-4c7e-ba58-ed2d867ac350 · outbound

This paper cites Rae, Oriol Vinyals, and Laurent Sifre.

Predicting Emergent Capabilities by Finetuning Rae, Oriol Vinyals, and Laurent Sifre

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.086105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11019e95-ddbe-4a2b-be7a-53e65d49abc4 · outbound

This paper cites Predicting Emergent Abilities with Infinite Resolution Evaluation.

Predicting Emergent Capabilities by Finetuning Predicting Emergent Abilities with Infinite Resolution Evaluation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.090662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97cb7e55-a901-4691-b164-15a24fb8b279 · outbound

This paper cites Compression Represents Intelligence Linearly.

Predicting Emergent Capabilities by Finetuning Compression Represents Intelligence Linearly

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.095518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a9e5b6-40a4-4275-9dc4-eb1faa5db8eb · outbound

This paper cites Scaling laws for downstream task performance of large language models.

Predicting Emergent Capabilities by Finetuning Scaling laws for downstream task performance of large language models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.100058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff26e04d-d338-4150-9cd5-8c0cc49b729f · outbound

This paper cites Scaling laws under the microscope: Predicting transformer performance from small scale experiments.

Predicting Emergent Capabilities by Finetuning Scaling laws under the microscope: Predicting transformer performance from small scale experiments

Reference 30

Resolution: verified exact; doi, observed 2026-08-12T13:41:46.302863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 787d0171-74af-4ad8-bf88-46834009ad46 · outbound

This paper cites Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei.

Predicting Emergent Capabilities by Finetuning Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.109591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e02d7550-b495-4f0e-a036-df8cf8ed6c5d · outbound

This paper cites Scaling laws for fine-grained mixture of experts, 2024.

Predicting Emergent Capabilities by Finetuning Scaling laws for fine-grained mixture of experts, 2024

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.114322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef47036-2955-4f45-a12a-09bfe1572ee8 · outbound

This paper cites Starcoder: may the source be with you! 2023.

Predicting Emergent Capabilities by Finetuning Starcoder: may the source be with you! 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.118767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3e3d0a9-620f-4da1-8b29-dfa44169a67e · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Predicting Emergent Capabilities by Finetuning Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.123561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43d13c81-2043-4e55-b0cc-ba2e7695e138 · outbound

This paper cites Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla.

Predicting Emergent Capabilities by Finetuning Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.127986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d66559c1-121c-4393-b3c9-eb2821b2443d · outbound

This paper cites Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel.

Predicting Emergent Capabilities by Finetuning Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.132683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d4a2e13-5f6e-46c9-8854-b6c0fcd8287a · outbound

This paper cites Scaling data-constrained language models.

Predicting Emergent Capabilities by Finetuning Scaling data-constrained language models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.136957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55ee2b1-e87f-48a6-b362-71fde885c6b1 · outbound

This paper cites In-context learning and induction heads.

Predicting Emergent Capabilities by Finetuning In-context learning and induction heads

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.141428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a092fa50-d1b0-4fe4-ab40-9565a7445e73 · outbound

This paper cites GPT-4 technical report, 2024.

Predicting Emergent Capabilities by Finetuning GPT-4 technical report, 2024

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:46.947634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd925cb2-8907-4699-9a2b-07d8148ed0e6 · outbound

This paper cites How predictable is language model benchmark performance?.

Predicting Emergent Capabilities by Finetuning How predictable is language model benchmark performance?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.150658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fc9b9d2-fcb2-4e02-b044-1ab668b818b7 · outbound

This paper cites Mark zuckerberg - llama 3, open sourcing \ 10b models, & caesar augustus.

Predicting Emergent Capabilities by Finetuning Mark zuckerberg - llama 3, open sourcing \ 10b models, & caesar augustus

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:46.930960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 14a1ad2d-0468-4e7e-ac37-a4e5fb48090e · outbound

This paper cites The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only.

Predicting Emergent Capabilities by Finetuning The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.158562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fec5bf8-afbc-4148-af84-70f969e6c9cd · outbound

This paper cites Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro.

Predicting Emergent Capabilities by Finetuning Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.162628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a678f03c-5545-4a5e-abe1-63c884567898 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Predicting Emergent Capabilities by Finetuning Code Llama: Open Foundation Models for Code

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.168477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc45107e-6534-48a5-8971-9e534aa10c14 · outbound

This paper cites Observational Scaling Laws and the Predictability of Language Model Performance.

Predicting Emergent Capabilities by Finetuning Observational Scaling Laws and the Predictability of Language Model Performance

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.173180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347eaa26-8492-4410-a809-82833ba07777 · outbound

This paper cites Are emergent abilities of large language models a mirage?, 2023.

Predicting Emergent Capabilities by Finetuning Are emergent abilities of large language models a mirage?, 2023

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.177815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5275730-b464-4408-b084-1b6691976be1 · outbound

This paper cites Active learning literature survey.

Predicting Emergent Capabilities by Finetuning Active learning literature survey

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:46.905574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a4db7fa9-1212-4148-b23a-0100283cd38f · outbound

This paper cites Model evaluation for extreme risks.

Predicting Emergent Capabilities by Finetuning Model evaluation for extreme risks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.186969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60c7a955-2b1c-4eb6-a189-75dab3117c47 · outbound

This paper cites Commonsenseqa: A question answering challenge targeting commonsense knowledge, 2019.

Predicting Emergent Capabilities by Finetuning Commonsenseqa: A question answering challenge targeting commonsense knowledge, 2019

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.191727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af491cf6-710f-405e-b125-5303224f4257 · outbound

This paper cites Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?.

Predicting Emergent Capabilities by Finetuning Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.196766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7b5ad2f-8d97-4ddb-b2d7-b0e890848129 · outbound

This paper cites Improving Pretraining Data Using Perplexity Correlations.

Predicting Emergent Capabilities by Finetuning Improving Pretraining Data Using Perplexity Correlations

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.201649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6134ecc2-51c7-4883-96e0-f0c1ea965a15 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Predicting Emergent Capabilities by Finetuning LLaMA: Open and Efficient Foundation Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.206648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50e6794f-4292-4e81-8ba3-343c525eb762 · outbound

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

Predicting Emergent Capabilities by Finetuning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.211796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77bc24d6-c32f-4f77-adfd-d493354b734f · outbound

This paper cites GLUE : A multi-task benchmark and analysis platform for natural language understanding.

Predicting Emergent Capabilities by Finetuning GLUE : A multi-task benchmark and analysis platform for natural language understanding

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.216633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47f4acdf-7304-4c34-a3c5-d4bf01a34ce8 · outbound

This paper cites Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus.

Predicting Emergent Capabilities by Finetuning Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:41:46.879690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c0ca1ec-6bee-447c-a509-59d58bcbfce1 · outbound

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

Predicting Emergent Capabilities by Finetuning Chain-of-thought prompting elicits reasoning in large language models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.225882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02c817c7-1e25-4563-88a2-6c11c8826ec6 · outbound

This paper cites Training Trajectories of Language Models Across Scales.

Predicting Emergent Capabilities by Finetuning Training Trajectories of Language Models Across Scales

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.230224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a334f3ac-e991-46f1-bdb9-22b042e9d5f4 · outbound

This paper cites Star: Bootstrapping reasoning with reasoning.

Predicting Emergent Capabilities by Finetuning Star: Bootstrapping reasoning with reasoning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.235064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91a1f6a0-b85b-4a5e-bb00-c14e5b359f87 · outbound

This paper cites write newline.

Predicting Emergent Capabilities by Finetuning write newline

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.239766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c099122-094d-4bb7-9f17-b8ed8142b730 · outbound

This paper cites @esa (Ref.

Predicting Emergent Capabilities by Finetuning @esa (Ref

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.245295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 366a5b0c-29f0-4d1f-85b1-4f9cee70b275 · outbound

This paper cites an unresolved cited work.

Predicting Emergent Capabilities by Finetuning Unresolved cited work

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T13:41:46.250303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88904a78-79d2-4695-8f36-a0215bb91b16 · outbound

This paper cites an unresolved cited work.

Predicting Emergent Capabilities by Finetuning Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:41:46.815064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 6ee9b21c-bb66-41d5-bc41-4c5df5b00050 · inbound

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation cites this paper.

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation Predicting Emergent Capabilities by Finetuning

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-15T17:21:06.992504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.