Pith. sign in

Paper Citation Record · LEDGER

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation

As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2505.19529.

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

pith.paper-citation-record.v1
2505.19529 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:17:13.982716Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T20:22:55.750693Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

50 of 50 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ba269e43-3d07-482d-9e57-8d183c7e61d0 · outbound

This paper cites Paligemma: Towards compact vision encoders for multi- modal models.Transactions on Image Processing,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Paligemma: Towards compact vision encoders for multi- modal models.Transactions on Image Processing,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:17.827205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.400821Z digest=sha256:5a7ad48dd9e786082da2b69362312046021f14790903a05576cbe1df0b74292c

Observation e57543c6-54ef-47d4-a4bd-08ba2221afcd · outbound

This paper cites In- ternvl2: Scalable multi-modal models with reduced vision encoder complexity.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation In- ternvl2: Scalable multi-modal models with reduced vision encoder complexity

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:17.607727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.455294Z digest=sha256:ee1dfbe1b0561f9c325f12998ab1bd34a6616d44e7e43940eeba7a7d078b6da2

Observation 525d393f-0f0e-47c6-b7b5-8a59b7d7bd7a · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.462045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.462045Z digest=sha256:f3ae03bfd3de626a8a2c79b907cf5ae493d90c563f8c603159f65b9e1cb1d2df

Observation 32760e6c-4e9b-4439-b832-db51f67a6641 · outbound

This paper cites Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.511088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.511088Z digest=sha256:b5937568803e43bf217eb0c229e8eed197292186cec8eeaa155593a4609d381c

Observation 9e20b6e3-3618-43d1-9032-172cf5660d5e · outbound

This paper cites RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.537923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.537923Z digest=sha256:5c7c5be03a13433e52b2e13a22417f8e8315334788f6b6f2d75a51c069e0736e

Observation 4d57117a-8ee2-4611-88a2-76b622201287 · outbound

This paper cites Hallusionbench: an advanced diagnostic suite for entangled language hallu- cination and visual illusion in large vision-language models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Hallusionbench: an advanced diagnostic suite for entangled language hallu- cination and visual illusion in large vision-language models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:17.071197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.622080Z digest=sha256:6af23f84d88f445718789cc4fdae2018f2464d51c571b023bafead91405cd0b4

Observation fea74fcc-4562-4db2-aa15-11db796590ed · outbound

This paper cites Learning both weights and connections for efficient neural networks.Advances in Neural Infor- mation Processing Systems (NeurIPS), pages 1135–1143,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Learning both weights and connections for efficient neural networks.Advances in Neural Infor- mation Processing Systems (NeurIPS), pages 1135–1143,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:16.844833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.624558Z digest=sha256:2491b9fc707a631faeb1b0a763dd93a30346149dee797971387921a939b7c039

Observation ff6090e1-6391-4622-93ba-414497b53be0 · outbound

This paper cites an unresolved cited work.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:17:16.646144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.682390Z digest=sha256:b1f377bcce941e23d39d2145c5b48c19ddc099e94f941973199adbb9499b73cd

Observation f8778558-a2fb-4087-b379-4913e0515162 · outbound

This paper cites Hooper and T.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Hooper and T

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:16.517334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.691663Z digest=sha256:4790e48db181edd16028c9a774cf2e143ed214a1356bf8548e31fc6e238c0ad4

Observation 1d13cc24-f49a-4213-8240-4295edffd042 · outbound

This paper cites The price of prompting: Profiling energy use in large language models inference.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation The price of prompting: Profiling energy use in large language models inference

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.707616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.707616Z digest=sha256:a77a1837400652f1d335467429b4453d75e22d22b1ec2a6cc289340e917c67f1

Observation bc43c28a-25c9-4381-8c83-bf0b92b7143b · outbound

This paper cites Distributionally Robust Receive Combining.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Distributionally Robust Receive Combining

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.711326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.711326Z digest=sha256:03b2ca514b46c077702f07a76e55ab643106cd5c454653d7596116a17506138b

Observation b72f986e-e1fa-4137-948d-6f3944b454e4 · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.727608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.727608Z digest=sha256:39cd2fe2ad69cccbd1fa7bcadf705681b46be7ff8c0e56679e62591bc3f94d8b

Observation 08c83d54-410e-45a5-b4c7-e695f2d79c0d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Adam: A Method for Stochastic Optimization

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.863978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.863978Z digest=sha256:353de207a2645afe0579383d8341c6ce7d2faacf821896c7d55521363a323a09

Observation 27f3e6c1-68fc-4035-9afd-f44d73be0d70 · outbound

This paper cites Idefics2: Efficient multi-modal fusion with lightweight visual encoders.Transactions on Pattern Anal- ysis and Machine Intelligence,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Idefics2: Efficient multi-modal fusion with lightweight visual encoders.Transactions on Pattern Anal- ysis and Machine Intelligence,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:16.234259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.055737Z digest=sha256:388faf5c0ee2657177f4e7bc2499581686a9b2c17afb1b45c2bdb2962a5cb591

Observation 3067529d-1b04-41d2-93d5-bf95167f3788 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.163973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.163973Z digest=sha256:7de144e590dce446dff9c9bb0d51a892311da55df23ea212699efc0ccf4c361a

Observation 981ae193-7e67-442a-9c3b-1bf192d17e9e · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.320067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.320067Z digest=sha256:8b9b5b848bef572be2b96593e09e800e2041e6e0147e7924d7999aea9c0aa839

Observation f737957a-7371-4b8e-aa36-43a5b9c3ab8f · outbound

This paper cites LLM-PBE: Assessing Data Privacy in Large Language Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation LLM-PBE: Assessing Data Privacy in Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.334623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.334623Z digest=sha256:1fce883f740d6d3596dee7beadb4d115f03d1701d3f88d221a20195209a1616b

Observation 0a63797f-8042-4a1f-9fa6-f06e84a5dd47 · outbound

This paper cites Sophia: A memory-efficient optimizer for large-scale model training.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Sophia: A memory-efficient optimizer for large-scale model training

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:15.892780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.352967Z digest=sha256:f1d713489dcd4314581fac4d7d96c59a2db9c19fc9e312cd7aa947b82ea64cc7

Observation c58d0578-9101-470e-9eef-932886b97af9 · outbound

This paper cites Prompt Injection attack against LLM-integrated Applications.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Prompt Injection attack against LLM-integrated Applications

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.481222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.481222Z digest=sha256:cbafd1f549a3f9fe83ffbf353c370508535c1d680fe2683efe9b8be4efafa752

Observation eb9bae79-ec57-4a33-8ce0-de74faecff51 · outbound

This paper cites Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.496846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.496846Z digest=sha256:9cb2c4df3027ea677066b4b5b9ef9f6dd07aa6ce6f805b68d219d8f53eca20a0

Observation 1d4ac386-14aa-4d58-aa36-a2e399a61ba2 · outbound

This paper cites Decoupled Weight Decay Regularization.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Decoupled Weight Decay Regularization

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.591921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.591921Z digest=sha256:e4c226b3102eeab7d798caa7814680c07891410c40f934d49814064c89225508

Observation 9d9c8a15-0f85-4924-8d95-e20f4bf3def6 · outbound

This paper cites Mono-internvl: Mlp-based architectures for efficient multi-modal fusion.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Mono-internvl: Mlp-based architectures for efficient multi-modal fusion

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:15.694658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.651520Z digest=sha256:320bba78fdb5d56bd1cc21634aad098481336e9af37818a2030ee1dd9738ca93

Observation 1aafba37-afd3-47b5-9cbb-b195ed8b7c2c · outbound

This paper cites Mixed pre- cision training.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Mixed pre- cision training

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:15.483641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.683775Z digest=sha256:f836550fa778d923b2e574f1b48d5302afa87ca9631b03787e5e441afe47055f

Observation 26686d04-756c-47ad-92a1-c9c358329c4a · outbound

This paper cites Characterizing power management opportunities for llms in the cloud.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Characterizing power management opportunities for llms in the cloud

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:15.242828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.854614Z digest=sha256:6aaf6002f392cd71832b9dbbfa872684a3b724f1ba25a6d97e9787279489dec6

Observation 7a85df90-f420-45fa-bcbc-c293d55f41b0 · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation RWKV: Reinventing RNNs for the Transformer Era

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.868317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.868317Z digest=sha256:195e1d375a96d92f4d0ad057689ae5fb9f7f7b42d5192f416b26370326ddd1b3

Observation f7bc1586-190f-42cd-8d59-7db0f3401569 · outbound

This paper cites Language models are unsupervised multitask learners.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Language models are unsupervised multitask learners

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:15.051946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.929444Z digest=sha256:d4fb4936824819d0baaa952ad5eb382dac9aadee81673d9cf6f97d0f5a2677e5

Observation 9c80f438-bf06-4bac-9da0-17b54e578f5c · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.000942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.000942Z digest=sha256:085a2b16ae3b5b156ff02765a988f21d8dbf5ec8a471f463c817182c6d1e4509

Observation 8c0302bc-9844-495f-9d82-d0cd79918f66 · outbound

This paper cites A primer in bertology: What we know about how bert works.Transactions of the Association for Com- putational Linguistics, 8:842–866,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation A primer in bertology: What we know about how bert works.Transactions of the Association for Com- putational Linguistics, 8:842–866,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:14.957140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:13.036025Z digest=sha256:7dae67f0dfec7216f8339bacf6c848dc730019713e17fbeca77038f531977e80

Observation 6bc4f6ac-cdfd-4a87-9005-923b38063684 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.080609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.080609Z digest=sha256:1df69715ba3902123f01dc5fd6aea722b669ab98a7cfb28d499dc5c4c1b396a1

Observation 22d5c83e-5765-4de7-84be-7ec87f3ab893 · outbound

This paper cites Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.163081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.163081Z digest=sha256:3e599eb29026c67098e5ed1f6d452db47534c1dc38d4343114b78b4aaf056dd6

Observation ff0c436f-f0f8-4b17-8539-95eacae40950 · outbound

This paper cites Dy- namollm: Designing llm inference clusters for performance and energy efficiency.arXiv preprint arXiv:2408.00741,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Dy- namollm: Designing llm inference clusters for performance and energy efficiency.arXiv preprint arXiv:2408.00741,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.228754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.228754Z digest=sha256:7a07282e2d05832266facebd0d7ce3124158e80c3c6dd4301c8584fa785459d4

Observation d664f92c-b996-4566-82f9-81bf444e72d0 · outbound

This paper cites Mobilebert: A compact task-agnostic BERT for resource-limited devices.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Mobilebert: A compact task-agnostic BERT for resource-limited devices

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:14.858591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:13.316281Z digest=sha256:6c5b68eebb22701a7dea84d49e4600cf11285848ee464ab3ed63563e5399c38e

Observation 13675588-4f3d-41a6-9065-15e4421d2be0 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation A Simple and Effective Pruning Approach for Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.388307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.388307Z digest=sha256:eeddc9bd1714ddbed80afe5fad7588f0ffae559519168a98a3d00e0866851375

Observation 7e41aa38-ff46-4ba9-8ab9-2384f277e640 · outbound

This paper cites Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.520349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.520349Z digest=sha256:ba4715313a63e8f76edbf3e8ac45cfeb7233d9d13740ca589b0825bfb947841a

Observation d2d3d269-a9a6-4263-9a70-464058ce7405 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:14.717813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:13.587314Z digest=sha256:a2a282dd9cf16e36de7d76fab7d45d834f5f869cc640fe2d029b0fb770c1bbb0

Observation d9f20b2c-fff4-424d-9f38-361bf038c52f · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.649125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.649125Z digest=sha256:5283b0806db1eba338d0d9a85f0af0ab994338bcca70fab431b8c838aed0d6fa

Observation 68daf60d-6e6b-400a-8df4-ab97fea72bc8 · outbound

This paper cites Privacy-Preserving Instructions for Aligning Large Language Models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Privacy-Preserving Instructions for Aligning Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.709783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.709783Z digest=sha256:39680e6028c83ec98b31e74555c5578c1f083f6e36e50d2fc160ab793ed1bf60

Observation 6295d597-242a-4e73-80ea-d1236c263649 · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.776915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.776915Z digest=sha256:954bd41ff55fe4a18f4aef6b01d852aa1fc91cf2f6a1fdf11603a076ae984d71

Observation ebdda103-2ce5-433d-b1b2-a713d540c036 · outbound

This paper cites TinyLlama: An Open-Source Small Language Model.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation TinyLlama: An Open-Source Small Language Model

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.851848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.851848Z digest=sha256:a9b753f6b32884a487b739ccaf230c8086e142640267f27aac7d282fc483f360

Observation bd81e855-636f-4768-bbaf-40464cf7f24e · outbound

This paper cites PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.922316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.922316Z digest=sha256:8073a9fe68fdd8e9b351105269cde836f28e7c172123b14ea9d430ca0fe978f8

Observation 3149eb77-4ecc-456d-83e6-c3e6e4ed1d8d · outbound

This paper cites FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:17:14.112359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:13.982716Z digest=sha256:8ea87426793a5915fa4756fd785682192ce0a821f17ac1c792e676ae25d3d4dc

Observation 451a2cec-ba0e-445a-b54e-ee7e56ad6f1e · outbound

This paper cites Reformer: The Efficient Transformer.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Reformer: The Efficient Transformer

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.954986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.954986Z digest=sha256:2ce03681911699bb95fa1d41b8e9fb168c1c3466b1b5f451c58ddcfa1dafd2db

Observation 18420bcd-1426-47cd-8f14-8638b35a56f6 · outbound

This paper cites Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.627462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.627462Z digest=sha256:5ebb8ec560ea1d1d5cdd62bf432894ee0ab5db89058d593a32e11a8b38c2cb13

Observation 412d6c06-8663-4262-a70b-d2b1a3d26820 · outbound

This paper cites BBQ: A Hand-Built Bias Benchmark for Question Answering.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation BBQ: A Hand-Built Bias Benchmark for Question Answering

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:12.731119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:12.731119Z digest=sha256:edb5c42f27e727bb8ab7168419784712a6781306fc8656b252ab48abcc133257

Observation f13f7814-9cee-49a6-a712-46a252697270 · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:16.387650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.784482Z digest=sha256:7a9e6ca7015e9bb20a1bb4cf32917d92bae7027ddcd8e652e5c0587f4e2106a6

Observation e5707c30-1294-496b-81ba-f9e3009b34fe · outbound

This paper cites Minillm: Knowledge distillation of large language models.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Minillm: Knowledge distillation of large language models

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:17.297578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.572309Z digest=sha256:0d6c5534bf08b67ddd71fc1c82d0a1dd9b66bcfb323325900947f6654e534253

Observation cc1cdb19-6f44-4ba1-8459-a4663bce7e02 · outbound

This paper cites Mini-gemini: Efficient multi-modal models with lightweight vision en- coders.Proceedings of the International Conference on Machine Learning,.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Mini-gemini: Efficient multi-modal models with lightweight vision en- coders.Proceedings of the International Conference on Machine Learning,

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:16.031243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:12.255383Z digest=sha256:13ef90f3f1b343c3a8d908129e31f6bbcd583764921b8b92765ce4a3cca97844

Observation 1b73d8c0-525e-4910-83c4-2e637df2c6c0 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.481150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.481150Z digest=sha256:b80e6d700eeffbd7e8e153f6f12c986c9e970587ca6621a0a8c1e612de3c1f63

Observation 409ed7a8-8a80-494a-bfd3-2994e99998b5 · outbound

This paper cites Transformers are ssms: Generalized models and efficient algorithms through structured state space duality.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Transformers are ssms: Generalized models and efficient algorithms through structured state space duality

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:17:17.457918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:17:11.458535Z digest=sha256:c8d4e53e5b063ed04feafbf8d1a283a8d23427fac1d91413c70505edc5b299fe

Observation c0ab66cc-894b-4d69-b9e9-54185a6c8210 · outbound

This paper cites Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs.

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:11.452316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:11.452316Z digest=sha256:e714cad64cff3ff48bea781d88f224f71621996fc427eddb31de07ad450d4c5b

Pith citing papers

Observation badbdbc5-1620-4e3c-a4d0-e4d8509464f9 · inbound

Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning cites this paper.

Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation

Reference 155

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:23:12.763744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-19T20:22:55.750693Z digest=sha256:c97d5f58e78dcdc2feb155534cffe7113c57de42955412826d8ec739e2418506