Paper Citation Record · LEDGER

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings

As of 31 July 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2605.07994.

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

pith.paper-citation-record.v1
2605.07994 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-11T02:31:35.595850Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T23:28:39.275525Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact3
verified fuzzy30
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation baa22577-097b-415c-875e-1396f6ba14c8 · outbound

This paper cites An empirical study of smoothing techniques for language modeling.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings An empirical study of smoothing techniques for language modeling

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.567273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation d13ec70f-81d0-47e3-9473-da68204e13e7 · outbound

This paper cites Note on the general case of the Bayes-Laplace formula for inductive or a posteriori probabilities.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Note on the general case of the Bayes-Laplace formula for inductive or a posteriori probabilities

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.537732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 4bcb15f0-2329-4100-a4a0-4b4a3a332d27 · outbound

This paper cites Estimation of probabilities from sparse data for the language model component of a speech recognizer.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Estimation of probabilities from sparse data for the language model component of a speech recognizer

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.542247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 74fd6e39-77c0-4661-b237-e7a9855ec0d0 · outbound

This paper cites Interpolated estimation of Markov source parameters from sparse data.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Interpolated estimation of Markov source parameters from sparse data

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.629436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation ebf1833b-b06f-4731-b3c0-5b5000b5158b · outbound

This paper cites Improved backing-off for m-gram language modeling.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Improved backing-off for m-gram language modeling

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.648083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation a0c3ecd6-2df1-4002-ac1a-f7b58a7c1ef9 · outbound

This paper cites Attention is all you need.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Attention is all you need

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.587171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 6da576c9-0aa2-4ba1-ba2c-14cc14084e17 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Efficient Estimation of Word Representations in Vector Space

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-11T03:15:56.966919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 711f0f30-d8d5-44f8-b6ef-0f168f07ca86 · outbound

This paper cites Distributed representations of words and phrases and their compositionality.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Distributed representations of words and phrases and their compositionality

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.551430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 13e2b3a3-1596-4c71-bda9-f9a29b6ab642 · outbound

This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2013/file/9aa42b31882ec039965f3c4923ce901b-Paper.pdf.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Available: https://proceedings.neurips.cc/paper files/ paper/2013/file/9aa42b31882ec039965f3c4923ce901b-Paper.pdf

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.547016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation cca7f837-23e8-4623-87c5-9d5b0a54f81f · outbound

This paper cites Improving language understanding by generative pre-training.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Improving language understanding by generative pre-training

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.559439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 64fd4d9d-12c6-4e74-952f-42850598024e · outbound

This paper cites Available: https://cdn.openai.com/research-covers/ language-unsupervised/language understanding paper.pdf.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Available: https://cdn.openai.com/research-covers/ language-unsupervised/language understanding paper.pdf

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.644499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 6bcc59ec-6ab9-48cc-86f8-e0436ecdb4e6 · outbound

This paper cites Towards competitive n-gram smoothing.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Towards competitive n-gram smoothing

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.651576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 2b6de64b-7709-4192-8e19-30094deda7d6 · outbound

This paper cites The role ofn-gram smoothing in the age of neural networks.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings The role ofn-gram smoothing in the age of neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.625883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 22d394cd-639e-4fbd-a939-c94323c809e5 · outbound

This paper cites Generalization through memorization: Nearest neighbor language mod- els.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Generalization through memorization: Nearest neighbor language mod- els

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.602909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation e8f864c5-81a6-4220-bd7a-57894d29e17d · outbound

This paper cites Why do nearest neighbor language models work?.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Why do nearest neighbor language models work?

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.610870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation e09819e1-c883-4248-8690-cb1fb9287c4b · outbound

This paper cites 38 325–38 341.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings 38 325–38 341

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.614513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 241ac5c4-ee0d-42be-b8cd-d915c2d026a4 · outbound

This paper cites Distribution estimation with side information.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Distribution estimation with side information

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:15:56.954118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1cabba53-627b-4616-8456-47abeb8fc8b9 · outbound

This paper cites Asymptotics of language model alignment.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Asymptotics of language model alignment

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.633523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 939dc9d8-1c57-4035-bf72-5d592da70504 · outbound

This paper cites GloVe: Global vectors for word representation.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings GloVe: Global vectors for word representation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.637778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 7a1fef59-af7f-4850-97eb-71a7240b10b6 · outbound

This paper cites Admissibility properties or Gilbert’s encoding for unknown source probabilities (corresp.).

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Admissibility properties or Gilbert’s encoding for unknown source probabilities (corresp.)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.599279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation d0057724-37f5-4af0-a140-458ccdddbcb3 · outbound

This paper cites The performance of universal encod- ing.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings The performance of universal encod- ing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.621969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 865c5b7b-1d4f-43b8-a0e3-7282b309be19 · outbound

This paper cites The Mixture Approach To Universal Model Selection.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings The Mixture Approach To Universal Model Selection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.607113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation dc267fd8-ff55-498b-a37a-9c63bf09e434 · outbound

This paper cites How to achieve minimax expected kullback-leibler distance from an unknown finite dis- tribution.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings How to achieve minimax expected kullback-leibler distance from an unknown finite dis- tribution

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.591620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation c6f33ad8-35b5-4900-a81c-8019e51258ea · outbound

This paper cites Variational minimax estimation of discrete distributions under kl loss.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Variational minimax estimation of discrete distributions under kl loss

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.654993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 23326843-0f8c-4046-a889-9acd3e6f98d6 · outbound

This paper cites Bernstein polynomials and learning theory.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Bernstein polynomials and learning theory

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.641234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 851304c2-db33-41f9-bff0-2374e4c2271d · outbound

This paper cites Pointer Sentinel Mixture Models.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Pointer Sentinel Mixture Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:10:32.318844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation d62008fb-fe6e-4bc4-8c29-4c3d5698b08d · outbound

This paper cites Datasets: A community library for natural language processing.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Datasets: A community library for natural language processing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.595569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation dfbb7d35-fe8e-479f-bc00-0df2e03bd734 · outbound

This paper cites Chebyshev polynomials, moment matching, and optimal estimation of the unseen.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Chebyshev polynomials, moment matching, and optimal estimation of the unseen

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.618559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation bff0c7e9-3648-4ed5-98d0-8a8acf9869f7 · outbound

This paper cites an unresolved cited work.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-05-14T12:25:15.583278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 4d709a53-fc22-4302-8be3-febdcdd471ec · outbound

This paper cites Yu,Assouad, Fano, and Le Cam.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Yu,Assouad, Fano, and Le Cam

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.563331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation deaf6e78-3ec3-4e58-820c-938953025b63 · outbound

This paper cites The Lipschitz constant of self-attention.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings The Lipschitz constant of self-attention

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.555270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation afa83194-99af-42a6-9868-b7ae12fb0b32 · outbound

This paper cites How smooth is attention?.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings How smooth is attention?

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.575770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation e06ca4f9-b16d-49f8-8d4e-e4093c9df6f4 · outbound

This paper cites 5817–5840.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings 5817–5840

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.579860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 09236d89-cb2a-4828-a728-608d427dc16a · outbound

This paper cites Mitigating transformer overconfidence via Lipschitz regularization.

Semantic Smoothing for Language Models via Distribution Estimation and Embeddings Mitigating transformer overconfidence via Lipschitz regularization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T12:25:15.571735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Pith citing papers

Observation d5c74ff8-21ea-43dc-ab00-e4736b340e36 · inbound

Inference-Time Consensus for Mitigating Hidden Behaviors from LLM Fine-Tuning cites this paper.

Inference-Time Consensus for Mitigating Hidden Behaviors from LLM Fine-Tuning Semantic Smoothing for Language Models via Distribution Estimation and Embeddings

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-07-30T23:28:39.275525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.