Paper Citation Record · LEDGER

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2608.09444.

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

pith.paper-citation-record.v1
2608.09444 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:26:53.877030Z

measured 31 of 31 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact3
verified fuzzy8
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 07d25cd3-f1e5-4507-8412-848e36fd7d10 · outbound

This paper cites The case for co-designing model architectures with hardware.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching The case for co-designing model architectures with hardware

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.789105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 088afc54-22b2-4fff-90dc-7b7c51bc9ccc · outbound

This paper cites Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.794727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2b8e30d-b719-4bef-90af-b6b593ac74b4 · outbound

This paper cites Mixture-of-recursions: Learning dynamic recursive depths for adaptive token-level computation.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Mixture-of-recursions: Learning dynamic recursive depths for adaptive token-level computation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.798373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bff012b2-d1d8-4338-8f49-b6fb8497de2f · outbound

This paper cites Pondernet: Learning to ponder.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Pondernet: Learning to ponder

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.801140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 753741f2-42f6-4fcb-bd56-86db4b8e597f · outbound

This paper cites Scaling laws meet model architecture: Toward inference-efficient LLM s.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Scaling laws meet model architecture: Toward inference-efficient LLM s

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.423545Z

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 df33bc29-1644-4ad8-ae69-6dbb772d0563 · outbound

This paper cites bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-11T17:26:54.279659Z

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 02c02286-f084-4583-805a-7d37db453be2 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Training Verifiers to Solve Math Word Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.810250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c420b19-2e83-49f5-80f8-32768cc50ddf · outbound

This paper cites Adaptive loops and memory in transformers: Think harder or know more? In Workshop on Latent & Implicit Thinking Going Beyond CoT Reasoning , 2026.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Adaptive loops and memory in transformers: Think harder or know more? In Workshop on Latent & Implicit Thinking Going Beyond CoT Reasoning , 2026

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.415921Z

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 ef472a37-498d-428b-8ac5-cb4bde71c066 · outbound

This paper cites Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.815625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6853c67-7e6d-4dc3-a47e-feba7b49319c · outbound

This paper cites Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, and Tom Goldstein.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, and Tom Goldstein

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.408249Z

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 92fafeda-e169-4a4a-b9e8-f36376cb7f6f · outbound

This paper cites an unresolved cited work.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.821396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eaf625f-7734-4716-b8cd-d91535f716f2 · outbound

This paper cites Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.824303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 450f3610-3738-4148-b99e-f309e2ccd511 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Efficient memory management for large language model serving with pagedattention

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.827094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d5002f9-3e51-4bb0-8e9d-c5940efec03f · outbound

This paper cites Sparse Layers are Critical to Scaling Looped Language Models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Sparse Layers are Critical to Scaling Looped Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.829565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eae1555-8ed8-4101-a38c-cf743b1ee22e · outbound

This paper cites Ponderlm-3: Adaptive token-wise pondering with differentiable masking, 2026.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Ponderlm-3: Adaptive token-wise pondering with differentiable masking, 2026

Reference 15

Resolution: verified exact; raw_fallback, observed 2026-08-11T17:26:54.192954Z

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 75ff262c-039a-48c8-845d-0da0641bcc9b · outbound

This paper cites Co TF ormer: A chain of thought driven architecture with budget-adaptive computation cost at inference.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Co TF ormer: A chain of thought driven architecture with budget-adaptive computation cost at inference

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.396219Z

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 ad71a3a8-e3a2-41fd-8f74-0acaaad2c10f · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.837099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a74457df-b3f4-44f8-9647-9986ca738d81 · outbound

This paper cites How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.839937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a960c856-479f-4e8b-a928-f084c9dfbdeb · outbound

This paper cites Flashattention-3: Fast and accurate attention with asynchrony and low-precision.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Flashattention-3: Fast and accurate attention with asynchrony and low-precision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.842642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45a25439-f503-460a-a12a-aba2e95c9d48 · outbound

This paper cites ShareGPT , 2023.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching ShareGPT , 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.384847Z

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 9dbee458-2f5d-47d6-8dfd-6456401816e7 · outbound

This paper cites Loopvit: Scaling visual arc with looped transformers, 2026.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Loopvit: Scaling visual arc with looped transformers, 2026

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.848072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a716a677-3d23-405d-9393-7f77573d4d87 · outbound

This paper cites Adaponderlm: Gated pondering language models with token-wise adaptive depth, 2026.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Adaponderlm: Gated pondering language models with token-wise adaptive depth, 2026

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.850843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20caf359-8308-4ce8-bce2-b44e9d6b9365 · outbound

This paper cites Michaelov, Chris, Chessing234, Hanwool Albert Lee, Janna, Leonid Sinev, Khalid, Kiersten Stokes, and Zdeněk Kasner.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Michaelov, Chris, Chessing234, Hanwool Albert Lee, Janna, Leonid Sinev, Khalid, Kiersten Stokes, and Zdeněk Kasner

Reference 23

Resolution: verified exact; doi, observed 2026-08-11T17:26:53.900773Z

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 74c28abf-0699-4ca1-8df6-c6dd9b9748f8 · outbound

This paper cites Sparse universal transformer.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Sparse universal transformer

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.856773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0391ffa2-8574-4df9-82e1-02603bc55cc5 · outbound

This paper cites Hashimoto.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Hashimoto

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.373762Z

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 20baffb5-6d18-4dd5-8451-7f5a8354d8d2 · outbound

This paper cites Recurrent-depth VLA : Implicit test-time compute scaling of vision-language-action models via latent iterative reasoning.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Recurrent-depth VLA : Implicit test-time compute scaling of vision-language-action models via latent iterative reasoning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.366259Z

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 a69a7bd4-7729-4b38-aba0-b2b9062f0def · outbound

This paper cites Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.865582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31f6872b-67a5-4257-87d8-92778a46b074 · outbound

This paper cites Roofline: an insightful visual performance model for multicore architectures.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Roofline: an insightful visual performance model for multicore architectures

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.868554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86448520-d82a-4a52-b769-286694514a76 · outbound

This paper cites Transformers: State-of-the-art natural language processing.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Transformers: State-of-the-art natural language processing

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.871322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a57946e7-11f6-4ad6-8262-701b53fa4ca6 · outbound

This paper cites Orca: A distributed serving system for Transformer-Based generative models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Orca: A distributed serving system for Transformer-Based generative models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:26:54.353756Z

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 368f2810-e0ac-4aa5-9843-89cae2bbf036 · outbound

This paper cites Scaling Latent Reasoning via Looped Language Models.

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching Scaling Latent Reasoning via Looped Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T17:26:53.877030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.