LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models | Paper Citation Record

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A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions cites this paper.

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 144

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:46:27.647448Z

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AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models cites this paper.

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 9

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E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning cites this paper.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 10

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Observation 911414fe-e58b-4241-b153-8be80d211849 · inbound

JPPO: Joint Power and Prompt Optimization for Accelerated Large Language Model Services cites this paper.

JPPO: Joint Power and Prompt Optimization for Accelerated Large Language Model Services LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 10

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Observation 451bc9a2-8be9-46c1-a39b-5fa59b2ba18a · inbound

JPPO++: Joint Power and Denoising-inspired Prompt Optimization for Mobile LLM Services cites this paper.

JPPO++: Joint Power and Denoising-inspired Prompt Optimization for Mobile LLM Services LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 16

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Observation 7794ffa5-db67-469b-b98c-b57fb734b362 · inbound

B-VLLM: A Vision Large Language Model with Balanced Spatio-Temporal Tokens cites this paper.

B-VLLM: A Vision Large Language Model with Balanced Spatio-Temporal Tokens LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 21

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Observation b1bc1a00-5a49-4a02-bf38-f9fe7df36884 · inbound

FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing cites this paper.

FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 2016

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Observation 0deb27a7-78d4-4780-8ed7-2568d03ebad0 · inbound

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness cites this paper.

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 18

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Observation 6afb25e3-bfd5-40c4-a724-80806a27129d · inbound

Compressed Chain of Thought: Efficient Reasoning Through Dense Representations cites this paper.

Compressed Chain of Thought: Efficient Reasoning Through Dense Representations LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-17T04:47:40.400393Z

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Observation ba44d3ee-c20e-4333-8ccd-0f54d631d154 · inbound

EvoWiki: Evaluating LLMs on Evolving Knowledge cites this paper.

EvoWiki: Evaluating LLMs on Evolving Knowledge LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 16

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Observation 6108fa53-a800-42be-9fb5-fa42c178d672 · inbound

EvoPat: A Multi-LLM-based Patents Summarization and Analysis Agent cites this paper.

EvoPat: A Multi-LLM-based Patents Summarization and Analysis Agent LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 20

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Observation 8b42b6be-e6f7-43dc-bd46-68648dccc2f4 · inbound

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG cites this paper.

Addressing the sustainable AI trilemma: a case study on LLM agents and RAG LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 64

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Observation d5a994b4-e873-4a42-8700-6d5efc7ef278 · inbound

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning cites this paper.

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 31

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Observation c0805d18-4818-4e42-8e52-cf6f52f50a36 · inbound

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation cites this paper.

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 21

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Observation e48c0a43-7e26-48da-9d2d-4c97cf3dd3fa · inbound

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention cites this paper.

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T23:46:30.078718Z

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Observation 6e2ceb50-3c8b-41dc-9d28-4039d3bc7f44 · inbound

Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation cites this paper.

Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 38

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Observation 030cb13d-2a63-4871-bc1b-00bf228d3047 · inbound

PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression cites this paper.

PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 16

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Observation 2cbcf88d-b56b-401c-8ef1-a4aad3be0a73 · inbound

MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAG cites this paper.

MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAG LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 12

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Observation e4058a9f-2dcd-4658-b504-75b78e3cd4c5 · inbound

Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models cites this paper.

Semantic Caching of Contextual Summaries for Efficient Question-Answering with Language Models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 11

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Observation 445cf6ed-50af-4bb1-a32e-798ee654dd31 · inbound

QwenLong-CPRS: Towards $\infty$-LLMs with Dynamic Context Optimization cites this paper.

QwenLong-CPRS: Towards $\infty$-LLMs with Dynamic Context Optimization LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 15

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Observation afafabaa-3390-46ed-81b2-6029bc351209 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 189

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Observation 7fb1ec33-d153-40f9-9093-18fd3a040d60 · inbound

SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling cites this paper.

SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 34

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Observation 0427e401-f35a-4281-b7c8-c7fb90d3b9e6 · inbound

Lossless Token Sequence Compression via Meta-Tokens cites this paper.

Lossless Token Sequence Compression via Meta-Tokens LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 9

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Observation 9fb66aae-c29f-4639-b5d7-2df33cc99457 · inbound

Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.

Cartridges: Lightweight and general-purpose long context representations via self-study LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 42

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Observation b22fdf2f-2736-4930-a9f5-d6438f68cbe7 · inbound

Brevity is the soul of sustainability: Characterizing LLM response lengths cites this paper.

Brevity is the soul of sustainability: Characterizing LLM response lengths LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 16

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Observation 12d84b6d-e533-4cd1-aaac-86815c522721 · inbound

LoRA-Gen: Specializing Large Language Model via Online LoRA Generation cites this paper.

LoRA-Gen: Specializing Large Language Model via Online LoRA Generation LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 2016

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Observation ea12e6e0-b53f-4cc3-a8ce-11b12b42f102 · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:17:24.592535Z

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

Observation d4cf843a-3838-4780-ac24-684bd888cb39 · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 24

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Observation 9c490a55-a641-41ed-979e-524003d7b96a · inbound

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression cites this paper.

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 16

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Observation cc7a1180-8b1d-4f7c-8378-d88f4f88a128 · inbound

How can we assess human-agent interactions? Case studies in software agent design cites this paper.

How can we assess human-agent interactions? Case studies in software agent design LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 20

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Observation 9fd21ffa-571e-4863-abbb-a76960a04134 · inbound

ARC-Encoder: learning compressed text representations for large language models cites this paper.

ARC-Encoder: learning compressed text representations for large language models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 19

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Observation 32c3b362-8b83-428a-a01d-689ab3ba003b · inbound

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents cites this paper.

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 45

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Observation 1840f4d0-04f9-4b48-9270-0fabf218d965 · inbound

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-21T13:44:11.449562Z

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Observation 33b6f1fa-13fa-4b47-9045-1a7d96d29872 · inbound

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 20

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Learning to Configure Agentic AI Systems cites this paper.

Learning to Configure Agentic AI Systems LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 8

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

Observation 10c5e7c7-b318-48a3-8ac3-99ae685b5df0 · inbound

Learning to Configure Agentic AI Systems cites this paper.

Learning to Configure Agentic AI Systems LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T11:31:29.533983Z

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

Observation b67fc6f0-ae67-4b8b-80ce-9d7915ae65f8 · inbound

LLM-assisted Agentic Edge Intelligence Framework cites this paper.

LLM-assisted Agentic Edge Intelligence Framework LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-15T14:00:03.440252Z

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.

Observation f698696a-d1b7-4447-b945-3c592ab986b2 · inbound

On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation cites this paper.

On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:40:27.553422Z

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.

Observation 3dc12810-508d-4da3-ab4e-f63eee353003 · inbound

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models cites this paper.

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:55:10.698328Z

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.

Observation d77242a0-5e09-4624-adee-921596b1bbc4 · inbound

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization cites this paper.

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:23:37.788133Z

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.

Observation ff9c3f20-8131-48f6-a877-a1e59cafc4cf · inbound

Supplement Generation Training for Enhancing Agentic Task Performance cites this paper.

Supplement Generation Training for Enhancing Agentic Task Performance LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T00:59:49.528114Z

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.

Observation 075c5251-e277-4d6d-aeec-c40261aeb228 · inbound

SparKV: Overhead-Aware KV Cache Loading for Efficient On-Device LLM Inference cites this paper.

SparKV: Overhead-Aware KV Cache Loading for Efficient On-Device LLM Inference LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:07.779041Z

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.

Observation a234ca39-dfe8-4eb4-b367-d6070dd1cf0f · inbound

OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory cites this paper.

OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:31:25.537117Z

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.

Observation 3726b935-c200-4b81-b842-0f3460351fb0 · inbound

Budget-Aware Routing for Long Clinical Text cites this paper.

Budget-Aware Routing for Long Clinical Text LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:26:10.192361Z

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.

Observation adc10e6b-b90c-4c19-b7d5-189f57fa8d6b · inbound

LLM-Oriented Information Retrieval: A Denoising-First Perspective cites this paper.

LLM-Oriented Information Retrieval: A Denoising-First Perspective LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:01:19.749858Z

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.

Observation c2fec4e9-8772-4d5f-9473-5a56d9782452 · inbound

LLM-Oriented Information Retrieval: A Denoising-First Perspective cites this paper.

LLM-Oriented Information Retrieval: A Denoising-First Perspective LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-21T00:19:16.570350Z

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.

Observation 570d6085-1061-43d9-ba01-bf90ae8330e2 · inbound

Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks cites this paper.

Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:26:24.196333Z

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.

Observation 0ce26496-205a-4f76-9f79-39760693bd75 · inbound

ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions cites this paper.

ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.513036Z

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.

Observation 7f1a60ae-bca1-40cc-b45f-89d97c3143b8 · inbound

Tool-Schema Compression Enables Agentic RAG Under Constrained Context Budgets cites this paper.

Tool-Schema Compression Enables Agentic RAG Under Constrained Context Budgets LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:24:01.270362Z

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.

Observation 94c48765-afd0-491c-8695-d7eb7ac9dc0e · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:26:26.695917Z

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.

Observation 53d80952-6f94-4501-b0fa-8058eeabff75 · inbound

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories cites this paper.

Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-13T07:44:25.325808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddddc700-5c17-4948-8aa4-b4d4e80ec9e8 · inbound

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving cites this paper.

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:46:57.478212Z

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.

Observation 2736a578-a94a-418a-9eeb-13cec35d42d4 · inbound

Decision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents cites this paper.

Decision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:25.260446Z

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.

Observation ca86e023-c913-4143-8476-247483c077a5 · inbound

End-to-End Context Compression at Scale cites this paper.

End-to-End Context Compression at Scale LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:17:31.616571Z

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.

Observation 38dda257-2d76-4c89-a68f-c7290b5a80a0 · inbound

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents cites this paper.

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:07:33.619433Z

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.

Observation 4555f900-c28b-4ff1-b6fd-9311a2aa28a7 · inbound

StaminaBench: Stress-Testing Coding Agents over 100 Interaction Turns cites this paper.

StaminaBench: Stress-Testing Coding Agents over 100 Interaction Turns LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:19:23.905129Z

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.

Observation e1434e72-7500-43ac-98d2-1752019b4273 · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:09:36.936832Z

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.

Observation a3c17276-531a-447f-b190-2fb8246f4ece · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 118

Resolution: unresolved; no resolver link, observed 2026-08-02T10:49:13.256103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06e93a9e-23a9-4284-a100-c4a53829084e · inbound

HMARS: A Hierarchical Multi-Agent Memory System for Long-Context Reasoning cites this paper.

HMARS: A Hierarchical Multi-Agent Memory System for Long-Context Reasoning LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:34:37.884491Z

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.

Observation 4404e395-a8a2-428c-8e87-7a2eed6babba · inbound

Mapping Text to Multiplex Graph: Prompt Compression as L\'evy Walk-Guided Graph Pruning cites this paper.

Mapping Text to Multiplex Graph: Prompt Compression as L\'evy Walk-Guided Graph Pruning LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T01:49:21.550972Z

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.

Observation b4d2f544-20d4-495b-ae9b-7a7cbd752945 · inbound

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair cites this paper.

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.569952Z

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.

Observation d4c13e6d-a18b-4ed4-bcea-7c1ee9e55a06 · inbound

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair cites this paper.

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-12T08:32:14.868469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 051587d5-d924-4796-a7b1-950773355e3a · inbound

Compression, structure, and executor capability: a controlled real-cost decomposition of language-model agent skill optimisation cites this paper.

Compression, structure, and executor capability: a controlled real-cost decomposition of language-model agent skill optimisation LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-12T05:14:41.315225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0bd2724-36b3-4170-98b8-ba9ce4697d40 · inbound

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents cites this paper.

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-07-10T01:36:44.323273Z

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.

Observation 410403c7-29ae-4e64-a6a4-897774022f78 · inbound

Mach-Mind-4-Flash Technical Report cites this paper.

Mach-Mind-4-Flash Technical Report LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-13T03:29:34.486347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a5f3d21-5cf8-4a9d-800c-d8a8c972387b · inbound

What Context Does a Coding Agent Actually Need to Act? cites this paper.

What Context Does a Coding Agent Actually Need to Act? LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T17:40:33.397259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd748da0-4d6e-40ff-9f9d-b36300ca1cc9 · inbound

Cache-Aware Prompt Compression:A Two-Tier Cost Model for LLM API Caching cites this paper.

Cache-Aware Prompt Compression:A Two-Tier Cost Model for LLM API Caching LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T23:14:54.635607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a17e1cd-b03b-4492-a933-1c39358fb63b · inbound

Shapley Context Pruning: A Cooperative Game Perspective for Context Reranking and Pruning cites this paper.

Shapley Context Pruning: A Cooperative Game Perspective for Context Reranking and Pruning LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T14:32:14.315923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e27cbc51-3fc1-4a48-905d-fe59b0e9ded6 · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-01T20:54:09.109669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0406970-d688-4c57-a030-8dbe36cf166a · inbound

Spectral-LSH: Sub-Quadratic Prompt Compression via Krylov-Projected Locality-Sensitive Hashing cites this paper.

Spectral-LSH: Sub-Quadratic Prompt Compression via Krylov-Projected Locality-Sensitive Hashing LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T11:37:06.990703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd698b93-d591-4e94-91ca-a68829c8f023 · inbound

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression cites this paper.

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:05:38.995166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2c13c4a-5ffe-4121-8948-f0309e808f58 · inbound

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents cites this paper.

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:03.120485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5a7c86-9ff8-40b0-b214-40f61224ee2d · inbound

AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups cites this paper.

AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T04:24:46.926491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers