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Paper Citation Record · LEDGER

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs

As of 9 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2507.03294.

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

pith.paper-citation-record.v1
2507.03294 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:21:07.216269Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

53 of 53 outbound references displayed

  • verified exact0
  • verified fuzzy41
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2711cb4d-48f0-45d5-8f1d-41db4681f6ba · outbound

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

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs LLaMA: Open and Efficient Foundation Language Models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 61231745-9146-4872-8648-8c4d998089af · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs OPT: Open Pre-trained Transformer Language Models

Reference 2

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Unavailable: canonical work link unavailable.

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Observation b528aff6-83ff-4d0f-947c-b574f8f67500 · outbound

This paper cites Mistral 7B.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Mistral 7B

Reference 3

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no resolver link, observed 2026-08-06T20:21:02.274329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5975ee0b-9d9b-4c2b-9a14-37de33e22b10 · outbound

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

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Chain-of-thought prompting elicits reasoning in large language models,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.392449Z digest=sha256:105d4833ea55ea676a4d19c48a4f013e7df2139a5fe091ee8ea17321c9e40e39

Observation 71005e53-b7b5-4f39-bf41-dfa43fa01c8d · outbound

This paper cites Gptq: Ac- curate post-training quantization for generative pre-trained trans- formers,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Gptq: Ac- curate post-training quantization for generative pre-trained trans- formers,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.471934Z digest=sha256:de8a9eb14d5a099de39973f37aad2aa8da626f9ed5d4f0a9133e0c952d08b85d

Observation 44da0740-5f0d-427b-8660-fa8073d4842f · outbound

This paper cites Awq: Activation-aware weight quantization for llm compression and acceleration,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Awq: Activation-aware weight quantization for llm compression and acceleration,

Reference 6

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raw_fallback, observed 2026-08-06T20:21:13.966042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.564450Z digest=sha256:781623ec4943d095f929bdd2924635de082035acb781c8c059d0b6f0f1f5195f

Observation 646ab0f3-2df8-4122-ad71-ac6b228ca72b · outbound

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

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs SmoothQuant: Accurate and efficient post-training quantization for large language models,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-06T20:21:13.690586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.637867Z digest=sha256:045cb65fd985b015da483f05d407bf8243cdf0e8566003fab5a5639655b4217a

Observation 40dca34b-8244-42af-b55b-98a5c7703172 · outbound

This paper cites Gpt3.int8(): 8-bit matrix multiplication for transformers at scale,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Gpt3.int8(): 8-bit matrix multiplication for transformers at scale,

Reference 8

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raw_fallback, observed 2026-08-06T20:21:13.416784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.696930Z digest=sha256:eda62193ba34d11fc78d0366871eb7a1eb7789a3bcdfdf9643877ad36cf4fbed

Observation 98a687c0-efe6-4e99-98ce-3b2eee773a97 · outbound

This paper cites Optimization-based post-training quantization with bit-split and stitching,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Optimization-based post-training quantization with bit-split and stitching,

Reference 9

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raw_fallback, observed 2026-08-06T20:21:13.251745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.775807Z digest=sha256:cc3c82e28ce6f4eaa7779f527755f9440b9a158a5f0a73e036ca34d9fdbb1211

Observation 8cc08662-9265-4411-b666-984ca2ff1b50 · outbound

This paper cites Llm-pruner: On the structural pruning of large language models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Llm-pruner: On the structural pruning of large language models,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T20:21:13.121687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.852961Z digest=sha256:c8238c3b8c7b2ad32ba66c8beb4e8c63cd750c8bcac13ce47fde5843eeedcf39

Observation 0d94868d-6928-4eaf-aea2-68ef7d1c38cd · outbound

This paper cites Fluctuation-based adaptive structured pruning for large language models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Fluctuation-based adaptive structured pruning for large language models,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-06T20:21:12.976674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:02.972938Z digest=sha256:24184fc6d8c5dbf723e084bbf7d483b802ec0a758d32c3dd25914783d6cfe38e

Observation 5aee30b7-0b3d-47cc-9bb8-6bc895773e22 · outbound

This paper cites Slicegpt: Compress large language models by delet- ing rows and columns,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Slicegpt: Compress large language models by delet- ing rows and columns,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.087068Z digest=sha256:467b07a13d99ad10ff7c43f4383e835b34ccc776fd14b96253c1d0f31752ecdd

Observation 87c9560b-684e-4005-85a1-5057f36e3357 · outbound

This paper cites Influence function based second-order channel pruning: Evaluating true loss changes for pruning is possible without retraining,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Influence function based second-order channel pruning: Evaluating true loss changes for pruning is possible without retraining,

Reference 13

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raw_fallback, observed 2026-08-06T20:21:12.751961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.211609Z digest=sha256:2965af32443706cd89dbe03553e0f2c221ef90fd034bc85f9000123c7142da0d

Observation 4d94f95d-b4c5-41dd-ba2a-0113879ce618 · outbound

This paper cites Performance-aware approximation of global channel pruning for multitask cnns,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Performance-aware approximation of global channel pruning for multitask cnns,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.335417Z digest=sha256:5b79464d3ece31180c74b757f8a7e0b3cafc775787c7e2d0590cc63b976ca0b7

Observation 02076452-c250-4522-b7f7-65ad91276e94 · outbound

This paper cites Can language models teach? teacher explanations improve student performance via personal- ization,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Can language models teach? teacher explanations improve student performance via personal- ization,

Reference 15

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raw_fallback, observed 2026-08-06T20:21:12.579244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.446821Z digest=sha256:606f2e3456ac9fa3f917dfb8152d9fe4030e6dec3d68687bd3ae7442284995e8

Observation 76378336-9c00-47a3-94a6-7d7c5cb303e8 · outbound

This paper cites Scott: Self- consistent chain-of-thought distillation,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Scott: Self- consistent chain-of-thought distillation,

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.515952Z digest=sha256:c8d613132707ba21d7015d82171b1c1ce2d6ea7603886f7a49f14273b2f2b779

Observation 31270c0a-0181-4e1d-b2c1-93b149692940 · outbound

This paper cites Unpacking the gap box against data-free knowledge distillation,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Unpacking the gap box against data-free knowledge distillation,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.621731Z digest=sha256:59341002235d73fa8b237ec9f24a79b60ae89b3fd398a6a641642eee9af7a760

Observation bcd5bf06-b12d-4824-b826-06001713bdfd · outbound

This paper cites Compressing transformers: Features are low- rank, but weights are not!.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Compressing transformers: Features are low- rank, but weights are not!

Reference 18

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raw_fallback, observed 2026-08-06T20:21:12.208051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:03.686481Z digest=sha256:454ca2d33dc2e09903674d71f939a514835be08fecf2f7cbdce7e71b4fcb7b7b

Observation 1db92442-57a7-4222-9246-382615498f7a · outbound

This paper cites ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:03.758040Z digest=sha256:269f42b94528308559d10c03413d2dc38a0e08098f1577affef822232e794f6a

Observation 76f4d2c8-cbb9-41b7-8317-4905b7b5f3ef · outbound

This paper cites SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:03.896534Z digest=sha256:7c457b236b06dc861b7a281782ac0a2ca1dfd24ef961d029969257b2a7d9f6f3

Observation a0811fc8-61f7-4195-87b9-1a085b69d673 · outbound

This paper cites Deeptensor: Low-rank tensor decomposition with deep network priors,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Deeptensor: Low-rank tensor decomposition with deep network priors,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.006657Z digest=sha256:8ad2f57298d8a2dd686a41a88bcb03afe7188d203087350538f2d1ee0a180b5a

Observation 92bef79e-3622-4936-a5af-137b043f63c2 · outbound

This paper cites Compressing pre-trained language models by matrix decomposition.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Compressing pre-trained language models by matrix decomposition

Reference 22

Resolution
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raw_fallback, observed 2026-08-06T20:21:11.961984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.147638Z digest=sha256:28f8ed6cfbdb253b2fb38a32745e2917e60860d624401d7d5a6e51b72bf8ba81

Observation bd5e81a5-cca7-4dbf-b83a-a7f8b8ae76e5 · outbound

This paper cites Drone: Data-aware low-rank compression for large nlp models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Drone: Data-aware low-rank compression for large nlp models,

Reference 23

Resolution
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raw_fallback, observed 2026-08-06T20:21:11.875788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.211537Z digest=sha256:47821320bdd8c4b70ea530be65b56be588a7fd5e01c318c77438f31314e429d0

Observation 572563a3-06a7-4ef4-b816-8fea55dc1809 · outbound

This paper cites Lan- guage model compression with weighted low-rank factorization,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Lan- guage model compression with weighted low-rank factorization,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:11.768913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.289747Z digest=sha256:762ca9470e38eb27c7a550950ade36b541b22b9b6569e9d15bf9b1e085c63126

Observation 1a52f741-27b3-4031-8bcb-c94cf8dfa24f · outbound

This paper cites Lorap: Transformer sub-layers deserve differentiated structured compression for large language models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Lorap: Transformer sub-layers deserve differentiated structured compression for large language models,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:11.624491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.353956Z digest=sha256:b983d34f04c76f490b8b2421366f1a27afc207dd96f51a2158a42c9bab80ae43

Observation bb627705-85a2-4a3f-8b06-dec49fa1981e · outbound

This paper cites LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression

Reference 26

Resolution
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no resolver link, observed 2026-08-06T20:21:04.421461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:04.421461Z digest=sha256:695863ab148d71ea0f8ed5ff4a51918a5c2ca93604452e3e6f65740253180e91

Observation 9e49a9e2-0f6e-4c0d-9b5b-13c5af6ee102 · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 27

Resolution
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no resolver link, observed 2026-08-06T20:21:04.559289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:04.559289Z digest=sha256:886606eae858b3cfb3bc24dd40634aac82a4ab03b62b3ab75dd07d9e995fd823

Observation 2698336d-5baa-4286-a5c8-8b7951a8dd9c · outbound

This paper cites The optimal bert surgeon: Scalable and accurate second-order pruning for large language models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs The optimal bert surgeon: Scalable and accurate second-order pruning for large language models,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:11.463753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.716499Z digest=sha256:c0a910e42f264c73fb59322fdba60d8a9837c64d06e194ef5b90a1552237258e

Observation 1f91aeef-e5c4-4e3b-b126-a88ea4d04f9f · outbound

This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Sparsegpt: Massive language models can be accurately pruned in one-shot,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:11.279651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:04.858243Z digest=sha256:e4aa24582594e56dda9868a8b8dcd55e518beb1fbb920502a102bb259355dd8b

Observation e8fea30d-7958-4824-9fb6-31abbe02d14e · outbound

This paper cites Pointer Sentinel Mixture Models.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Pointer Sentinel Mixture Models

Reference 30

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unresolved
no resolver link, observed 2026-08-06T20:21:04.955287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:04.955287Z digest=sha256:92705b0f0e8f19aeab9ea4250c9ce3d961f08bbbc6a3553b2466afeb529830ec

Observation 314282d3-8e15-4068-98b6-e086dafe8137 · outbound

This paper cites Stanford alpaca: An instruction- following llama model,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Stanford alpaca: An instruction- following llama model,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T20:21:11.097673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.092121Z digest=sha256:a8efb56f34f2d4e1dada7ff5ba7bb6aa6a7f514f6a6dc1efff8d3ed30880c521

Observation af1a6d62-c46e-4064-925f-fff9ee21f614 · outbound

This paper cites Boolq: Exploring the surprising difficulty of natu- ral yes/no questions,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Boolq: Exploring the surprising difficulty of natu- ral yes/no questions,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.920024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.192188Z digest=sha256:8c9cb96960f2e013861460fd8d0e156938774b75e189318cba4efa03f712eba6

Observation c946e15a-b42f-4dc9-b8b0-52cb594f0338 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Piqa: Reasoning about physical commonsense in natural language,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.768825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.298509Z digest=sha256:bde7dea93c15cd5c79911a14d6bf9a2be2b3743f741a6442b73f3c64bcea41c5

Observation aacf1444-fbb5-4c5b-a7db-d6f5f1ac714d · outbound

This paper cites Hel- laswag: Can a machine really finish your sentence?.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Hel- laswag: Can a machine really finish your sentence?

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.577582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.368583Z digest=sha256:216d17f7935bb7f00b10d80850920a41582a42dab7a3fc482df10180277d026a

Observation 70638490-05d0-4b3e-b9cc-43b1b2e5c12f · outbound

This paper cites Wino- grande: An adversarial winograd schema challenge at scale,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Wino- grande: An adversarial winograd schema challenge at scale,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.408509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.464062Z digest=sha256:0c972a02f39068e56ee1722ed7978a6c36f9239043e57579e269775bf7474434

Observation f1e0d004-6b4d-468f-b0c5-d74ddea2596d · outbound

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

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T20:21:05.542157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:05.542157Z digest=sha256:557ea8c70e8a13acba8feb96cf87cc325bdb452e10d6c134d3456210e0e418f9

Observation 2cf040ac-cca7-4aef-adde-e096428f3b62 · outbound

This paper cites Can a suit of armor conduct electricity? a new dataset for open book question answering,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Can a suit of armor conduct electricity? a new dataset for open book question answering,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.245805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.652094Z digest=sha256:c3752977a5f1006fd17ca1c2a9cc16a582c4763c014dcd4779051c8fc61d5d26

Observation 9e3c559f-50a1-473c-bfd9-db3032405853 · outbound

This paper cites A framework for few-shot language model evaluation,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs A framework for few-shot language model evaluation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:10.074548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.714578Z digest=sha256:73dd646bcf1a40ce873e622f9cc2f6de8125434df865393b557ea8737a92568c

Observation 5e8e2ad3-33a5-415d-bfb0-26c6632f2d6e · outbound

This paper cites Data-free Weight Compress and Denoise for Large Language Models.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Data-free Weight Compress and Denoise for Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T20:21:05.872245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:05.872245Z digest=sha256:5e82132c00c551f6974c2be2fd84318428a74feb2b3d749ca22d64bce3bc068d

Observation b729450a-a5d9-4770-b194-b360ab4a6c76 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.893054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:05.963274Z digest=sha256:159469cd26df1bc52689dc65b8a3e76e8394bcfcad77102c8e0419512f16bd71

Observation e7d5f098-3071-414c-8231-5e36ea782778 · outbound

This paper cites Building a large annotated corpus of english: the penn treebank,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Building a large annotated corpus of english: the penn treebank,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.685394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.084205Z digest=sha256:0d348813a84a395ff4392e7053339edfb40d553672f8d6bbfdf285fe544bd621

Observation b465b81b-6bc6-4420-aeac-f5418a1e4b21 · outbound

This paper cites Improved baselines with visual instruction tuning,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Improved baselines with visual instruction tuning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.533595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.170122Z digest=sha256:540ec5980768215b63900cc3d4df8271862952e9ca4ce13991214432e7caf41e

Observation 48ce78c6-5d45-4b2f-97f1-060b8ca86f07 · outbound

This paper cites Vicuna: An open- source chatbot impressing gpt-4 with 90%* chatgpt quality,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Vicuna: An open- source chatbot impressing gpt-4 with 90%* chatgpt quality,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T20:21:06.245672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:06.245672Z digest=sha256:f6aac0db944b4a6b96c24ddfb88ec1c7498a09673681181f93b4d997fdda6153

Observation ffdb71e9-d520-4bd4-b10a-a9ff51d4860a · outbound

This paper cites Mak- ing the v in vqa matter: Elevating the role of image understanding in visual question answering,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Mak- ing the v in vqa matter: Elevating the role of image understanding in visual question answering,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.377222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.383749Z digest=sha256:9e2d52afbac71279e4c14bf4bab4041f9d6dee24df76c3390cc3d7320479a5b6

Observation deedccad-2ded-4c13-923d-cd673b86fa43 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.195532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.467209Z digest=sha256:cfadc4ec3ed2536b360c01ebe25c7bfd381609367301843b6516a06dd643310b

Observation bd2ad765-ab8f-4eff-b0f6-665c9568139a · outbound

This paper cites Learn to explain: Multimodal reason- ing via thought chains for science question answering,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Learn to explain: Multimodal reason- ing via thought chains for science question answering,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:09.010805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.539105Z digest=sha256:9ef2702db44d29455893f52bbc31977c067fb0d44779f0e3ee0c662b14544ae2

Observation 9bf9334f-1286-4545-a199-503234cb3958 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T20:21:06.617616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:21:06.617616Z digest=sha256:92ed6d6ab47a55c5fe565418c885e853dfa907d0c3877bdd475b14242c5aada2

Observation 14762086-5114-4f41-9954-db7149368625 · outbound

This paper cites Chartqa: A benchmark for question answering about charts with visual and logical reasoning,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Chartqa: A benchmark for question answering about charts with visual and logical reasoning,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:08.778988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.692848Z digest=sha256:23fdce9cf0ede5f988598254bcbab90dc380b8be366af728deba4e5be1098988

Observation 23a42079-183c-4b9c-a5d8-8f2242ec2fb1 · outbound

This paper cites Infographicvqa,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Infographicvqa,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:08.531677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.761393Z digest=sha256:fbaaf14c03c0a70ce4bb4a7a85ca8d38b44b520d4161eae4491929d780190364

Observation 161e45a7-1765-404f-9f90-a0ef4b4562a9 · outbound

This paper cites Ai2d-rst: a multimodal corpus of 1000 primary school science diagrams,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Ai2d-rst: a multimodal corpus of 1000 primary school science diagrams,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:08.344897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:06.888268Z digest=sha256:b3e88c76f803f74baf0c19b02b4160dce6598bea4e95ef047bb0fafa1fe2b2e6

Observation e9334916-609d-4e21-ba36-a563b95343f6 · outbound

This paper cites Vizwiz grand challenge: Answering visual questions from blind people,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Vizwiz grand challenge: Answering visual questions from blind people,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:08.084843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:07.021868Z digest=sha256:39c43742b1b0b93ab8db21b47b2097bfa21c62366525ae075d6872c0f36f2a65

Observation fe18faf9-a158-4335-8e37-3793f55e0f4c · outbound

This paper cites Towards vqa models that can read,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Towards vqa models that can read,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:07.882324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:07.110598Z digest=sha256:22a54dd5277625c129c81bcdc95aa4e7283ddf4c97b83f1006f521c11f66174e

Observation cddcb36f-713d-44ad-85da-958195d1e7c0 · outbound

This paper cites Lmms-eval: Accelerating the devel- opment of large multimoal models,.

MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Lmms-eval: Accelerating the devel- opment of large multimoal models,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:21:07.710885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:21:07.216269Z digest=sha256:7b27c2a62f5413d34cb3ee55d53c5d51e8aacd4cd042400727294210b3080503

Pith citing papers

No inbound Pith citation observations are available.