Pith. sign in

Paper Citation Record · LEDGER

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models

As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2504.15721.

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

pith.paper-citation-record.v1
2504.15721 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:25:34.557499Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e35b5ae-67ea-4d41-a7a9-0c2e5c71d0b4 · outbound

This paper cites Language Models are Few-Shot Learners.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Language Models are Few-Shot Learners

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.338551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.338551Z digest=sha256:afd0fb04c667de3da4b7f5669c9799c4265016c583ccbd0d30692da3b94f9a24

Observation d7c484a1-15c9-494a-90b6-7d5b78837b29 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Photorealistic text-to-image diffusion models with deep language understanding,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.344392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.344392Z digest=sha256:0f31977098790279db168e5f37b673200389c6cd5325b0d2f26033e928177d45

Observation 39e220f7-e918-4ce2-ab79-d98dcf966a1d · outbound

This paper cites Prestu: Pre-training for scene-text understanding,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Prestu: Pre-training for scene-text understanding,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.237190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.349479Z digest=sha256:52fb7e05b04f5e8e4c20298d20b952c81e72400c91cb64c679bb3e4248080ef1

Observation 613618c0-137e-42b4-93e0-f3651bb7f706 · outbound

This paper cites A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.355297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.355297Z digest=sha256:2f78200357684018233867fdc72eef1d3322d1d495de41b6671e4ea7a172aede

Observation 21fdf74d-d39d-46fd-b6a3-39d449f36be5 · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.360696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.360696Z digest=sha256:0f3df98790e2b3e9d0ec32af15be53bb0e7b20e147b2f652941b96c4183c0307

Observation e6bed82c-e099-41e4-8b86-42808825b167 · outbound

This paper cites A Survey on Efficient Inference for Large Language Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models A Survey on Efficient Inference for Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.366056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.366056Z digest=sha256:0df0d7acf7db6eed6ea6288e3ef69a117f9254650a442110a2c506f81b52f96a

Observation 0657d70c-d9d3-486f-849e-0f069ac08e59 · outbound

This paper cites Hardware Acceleration of LLMs: A comprehensive survey and comparison.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Hardware Acceleration of LLMs: A comprehensive survey and comparison

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.372035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.372035Z digest=sha256:b30a880ff4623bc3385ade4fb7737daf75ba82207fc7b1bb36e28199547fe461

Observation 49985ea2-facb-4b19-bce2-f7d1f880acab · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.377373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.377373Z digest=sha256:4732adf83a6d9bd8f70723ba8f8b13cc525bb1a63b24299ce8b57da556f12b89

Observation 484ca925-0908-4034-98ef-c2f8bde5a069 · outbound

This paper cites BiLLM: Pushing the Limit of Post-Training Quantization for LLMs.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.382890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.382890Z digest=sha256:cfa505b3dcc46d1d56ec4bce5ff17757edef7bfb38c464bbd3a8e26c931bbfaa

Observation 9f704969-ddb0-4ce4-a7a0-522cf204d750 · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.387988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.387988Z digest=sha256:ded28f62233f7acb5dc0ec9545c1004e879d5c9da537a49d77178c332a6cd426

Observation 1cb4e4ee-6ad2-465d-9ec0-2a44c7aa4d31 · outbound

This paper cites RPTQ: Reorder-based Post-training Quantization for Large Language Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.392958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.392958Z digest=sha256:b9d96eabbe62809eac424256a8e1d930e2dbc3717ed4ee8e55fe71796c72dafe

Observation beda1e26-dc25-43c3-bb44-ff4ee26f2367 · outbound

This paper cites GPT-4 Technical Report.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models GPT-4 Technical Report

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.398184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.398184Z digest=sha256:c2998b7bbaa77788f45742680416a4faca700d12befe3e6dcb075ff41dca1811

Observation e1ed57a6-a9a1-404d-a479-0fc9532604be · outbound

This paper cites Bfloat16 processing for neural networks,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Bfloat16 processing for neural networks,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.210357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.402997Z digest=sha256:e9646a8dd29cc5b0bb57d8f658a9986ca15495dd69703ccbbd907d51ba5c00e0

Observation 53c5d014-df9b-4116-aa47-3516b3d3e275 · outbound

This paper cites FP8 Formats for Deep Learning.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models FP8 Formats for Deep Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.407823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.407823Z digest=sha256:90b030a292904a84b67f8a7169d083aca540649f8bb852eb6b5acef5273d0216

Observation 52ea92a6-a352-4b9d-9ecc-3d40eaec762a · outbound

This paper cites Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.412775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.412775Z digest=sha256:f6e1cd2294a8b11b030f20eebebacc8e6fc1ee1879b34f4d54f43aaea1b877c2

Observation 6a1259f5-b035-4696-ace1-d103768c3f71 · outbound

This paper cites Be like water: Adaptive floating point for machine learning,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Be like water: Adaptive floating point for machine learning,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.195068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.417554Z digest=sha256:f916a6e16a3f3393761d092af71df7859b92713c62c9f72090abd7b5c59cee33

Observation 1a96266c-2268-45d7-bd20-6bfa1928b2df · outbound

This paper cites A block mini- float representation for training deep neural networks,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models A block mini- float representation for training deep neural networks,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.422444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.422444Z digest=sha256:278aef1709411dae1a7720708b6f8d34d2d82367381e08efc098daf452d8fdfa

Observation 6202a589-7db0-4ce8-8bda-3896bff0a77a · outbound

This paper cites Bie: Bi-exponent block floating-point for large language models quantization,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Bie: Bi-exponent block floating-point for large language models quantization,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.167745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.427559Z digest=sha256:7b4754494f3375809fc2ba965efc9f64642d3b4c0a9a5595db78bee7afd849b3

Observation 1cd7edd2-6eef-4b58-920e-79701994f99d · outbound

This paper cites Fpga-based convolutional neural network accel- erator with resource-optimized approximate multiply-accumulate unit,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Fpga-based convolutional neural network accel- erator with resource-optimized approximate multiply-accumulate unit,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.151517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.432785Z digest=sha256:c63264b8ee61dea10171f298e5b486cfeaead098b43bcfd8f0b9bcf6122cc5a9

Observation 507b34e2-4294-4127-b61e-c1528e147ba5 · outbound

This paper cites High-performance acceleration of 2-d and 3-d cnns on fpgas using static block floating point,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models High-performance acceleration of 2-d and 3-d cnns on fpgas using static block floating point,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.136034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.437579Z digest=sha256:1ce731270c9acb28b8995135a26ee3147fad64be318203d880cea287ab5d3a91

Observation 3e8a14af-00ae-4913-b2ea-dabc2639bb80 · outbound

This paper cites Computation error analysis of block floating point arithmetic oriented convolution neural network accelerator design,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Computation error analysis of block floating point arithmetic oriented convolution neural network accelerator design,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.120122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.442325Z digest=sha256:9987c71e19e44ad88cd6792da597d42478977b4deb20ec5dfa5c166c69684f4a

Observation b86dedc2-a213-4235-ac30-e7adea9ac2c1 · outbound

This paper cites Attention is all you need. advances in neural information processing systems,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Attention is all you need. advances in neural information processing systems,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.103984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.447220Z digest=sha256:f638f9480b3e9c696a67d3286a11b76c234f3ee738f019276b24d4bff6740b2f

Observation fcb56abd-b5eb-4121-bd41-a88ee93b3e0c · outbound

This paper cites Softermax: Hardware/software co-design of an efficient softmax for transformers,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Softermax: Hardware/software co-design of an efficient softmax for transformers,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.452166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.452166Z digest=sha256:bb4f2a09d2f3aee44c0a03854834cdf7e3e50c32ba4fe1944248303000bd7806

Observation 3e7c7b01-b98c-4954-89ce-1214b746c4bd · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models OPT: Open Pre-trained Transformer Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.457197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.457197Z digest=sha256:5e9732822fd76fa606286d1e94fdfa31b0037b1e59aabe3c64ff422286a030b1

Observation bf87f6a6-3364-494c-817e-3ff8d29ebd7d · outbound

This paper cites LLM-FP4: 4-Bit Floating-Point Quantized Transformers.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.462176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.462176Z digest=sha256:24dcaf74b36f6f369ebb6937612f4321db287bcebadcd10d92e4af21f6629be9

Observation 5bc6836b-e31e-4d00-8b76-50e3d29b0e42 · outbound

This paper cites I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.467393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.467393Z digest=sha256:213705284d5404b4a26b11daa21d3984ca2f16e267cf2130f781cc418e2e0b32

Observation b7ed3b85-23aa-49a1-b336-e65518f3e384 · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.472453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.472453Z digest=sha256:12f1897be33a91f9fab7bc55abde786d1f4964a8dd2f4091ce1889cc29908ec2

Observation 79099c03-2991-478d-8852-fdd06a4c2567 · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.477242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.477242Z digest=sha256:5582983ac98ae19addd8327dde5897756fc3c78193838d572c1f1df40d83d982

Observation 2dd6cbaa-7014-45ef-aef1-ad8307be7d12 · outbound

This paper cites Post-training quantization for vision transformer,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Post-training quantization for vision transformer,

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.482269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.482269Z digest=sha256:a5469761a24ff06980e9449f9655a0dd381c35476d5639a158264c7cd28566f6

Observation cc48e24d-4ad2-476c-8083-5c462c3d32d4 · outbound

This paper cites Q8bert: Quantized 8bit bert,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Q8bert: Quantized 8bit bert,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.487209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.487209Z digest=sha256:808f9203037c6aee92ea61bc983b72750e514bcf1153dd365d341c096a520d0a

Observation fb03534d-8518-4aca-a69e-46e7d9d3534a · outbound

This paper cites Roundoff errors in block-floating-point systems,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Roundoff errors in block-floating-point systems,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.045398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.492187Z digest=sha256:5e123cb3ca52d815eb99d24d4d2f499b818b6f8d26e9e91d753c260410829804

Observation ad8f230e-d3ff-46b8-a1d0-288fd713c850 · outbound

This paper cites A pseudo-softmax function for hardware-based high speed image classification,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models A pseudo-softmax function for hardware-based high speed image classification,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.028683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.496937Z digest=sha256:2f748385529336c182a0db231c29366c1b0bb14aaed6625280713cd9d6b9b8f7

Observation 14982851-8f09-4422-8054-42ac34536d95 · outbound

This paper cites High- precision method and architecture for base-2 softmax function in dnn training,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models High- precision method and architecture for base-2 softmax function in dnn training,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:35.012206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.502215Z digest=sha256:a0b3ad6f090addeb3624ceafc6371df48952865c93d269186ddd0d0901c4604e

Observation 35c169c6-a241-4ca2-a017-6681ad152d6a · outbound

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

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.507306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.507306Z digest=sha256:f090845b593c220dc37c912d6f508a7bcba837bc6ad03bf99eb5ae43633f20f2

Observation dbb42179-12f6-47c8-9529-edafe4d19bce · outbound

This paper cites Meta llama 3: Advancing generative ai responsibly,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Meta llama 3: Advancing generative ai responsibly,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:34.995309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.512904Z digest=sha256:d80ff9f139e8d54afd95d5a8dc017a09c6f21d95c130dfb85d28e545a3c530b0

Observation 5956a184-b1c5-455d-917f-3468cfe1c587 · outbound

This paper cites Pointer Sentinel Mixture Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Pointer Sentinel Mixture Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.518041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.518041Z digest=sha256:4672b67e6cf20a0f3b2acf2265b9bfcfad92db2718e5547624a1b7dc8596baf2

Observation d22831c2-b271-4ff3-9397-15098d2b1193 · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.523844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.523844Z digest=sha256:b56cebaad70359554201274092c10a6d8a7f19988198be85a532cd0882c40efc

Observation bfbcd621-962a-49cb-a730-f47c6af68ae7 · outbound

This paper cites Oltron: Algorithm-hardware co-design for outlier-aware quantization of llms with inter-/intra-layer adaptation,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Oltron: Algorithm-hardware co-design for outlier-aware quantization of llms with inter-/intra-layer adaptation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:34.978939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.530381Z digest=sha256:f9153c55c7e5e9ebeef0638083984bc0541f30e436cd8bf2e31b43e695fcff52

Observation 5fac0286-68d1-4f26-879d-706b30560c9f · outbound

This paper cites Olive: Accelerating large language models via hardware- friendly outlier-victim pair quantization,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Olive: Accelerating large language models via hardware- friendly outlier-victim pair quantization,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.535521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.535521Z digest=sha256:9d21b176191f84fba84e9048682c34a9dbc5b32372f1008d036c58ee0149d2f5

Observation 1e868da2-a803-4b6c-ac0b-3dc3fd7156f1 · outbound

This paper cites Chisel: constructing hardware in a scala embedded language,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Chisel: constructing hardware in a scala embedded language,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.540610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.540610Z digest=sha256:1cd63caf60b554004895a6bd24e7ccccc0ea01c65fc1e70329fc2e11cc8f3520

Observation ff1166d4-5689-4299-81f7-0a71c8abd3ad · outbound

This paper cites Kurup and T.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Kurup and T

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.546798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.546798Z digest=sha256:8c0819731fcffa5c09abfc9ef93513c9062b588a593dcc9d3114b859e2baec2c

Observation 1efb1af5-2283-4839-9372-7e92570c7d3d · outbound

This paper cites Cacti 6.0: A tool to model large caches,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Cacti 6.0: A tool to model large caches,

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:34.552197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:34.552197Z digest=sha256:1b3e7d3f92c23d9e15fddcac0f536fcda902b294b5d31d03f5f06b0379a230d4

Observation 1d5b1a50-c411-4cfa-89f2-a06bdfd898c1 · outbound

This paper cites Dnnweaver: From high-level deep network models to fpga acceleration,.

BBAL: A Bidirectional Block Floating Point-Based Quantisation Accelerator for Large Language Models Dnnweaver: From high-level deep network models to fpga acceleration,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T11:25:34.918108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T11:25:34.557499Z digest=sha256:091799bd33cd03928e7d52947691f1348d2145441bcb649fb706613184922e5d

Pith citing papers

No inbound Pith citation observations are available.