E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning | Paper Citation Record

Observation e9079c09-22fe-409f-a697-c0c9dd68b886 · outbound

This paper cites Mt-bench-101: A fine-grained benchmark for evaluating large language models in multi-turn dialogues.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Mt-bench-101: A fine-grained benchmark for evaluating large language models in multi-turn dialogues

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.647920Z

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Observation 4d9f9d2b-2e67-4e7d-8938-bf9581d91b2d · outbound

This paper cites Repocoder: Repository-level code completion through iterative retrieval and generation.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Repocoder: Repository-level code completion through iterative retrieval and generation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.644285Z

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Observation 3fad1377-82b8-4b1b-96be-13b56aa67003 · outbound

This paper cites Open domain multi-document summarization: A comprehensive study of model brittleness under retrieval.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Open domain multi-document summarization: A comprehensive study of model brittleness under retrieval

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.584642Z

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Observation cb0b5a6e-9236-4d3d-8a33-6e45746140b1 · outbound

This paper cites End-to-end training of multi-document reader and retriever for open-domain question answering.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning End-to-end training of multi-document reader and retriever for open-domain question answering

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.591533Z

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Observation bee035b7-d82f-416a-b8bf-565f0d9ac0fe · outbound

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

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Chain-of-thought prompting elicits reasoning in large language models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.640579Z

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Observation 0f97e1e2-508c-4f0c-90f1-67d95a7f5c82 · outbound

This paper cites A Survey on In-context Learning.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning A Survey on In-context Learning

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.062998Z

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Observation 3b826ad6-178b-4a5e-969f-0f5c59393dac · outbound

This paper cites A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.972280Z

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Observation 439792f7-6dac-47dc-908b-f657d5c97bd6 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Roformer: Enhanced transformer with rotary position embedding

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.625657Z

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Observation 2b9ac288-1bbf-4d44-9b4c-b69898b0c81b · outbound

This paper cites Longrope: Extending llm context window beyond 2 million tokens.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Longrope: Extending llm context window beyond 2 million tokens

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.617847Z

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Observation 038d4429-156d-4e4e-89ce-8cdbf1905052 · outbound

This paper cites LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models.

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

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.967159Z

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Observation a45ab5f7-dbf3-4c87-97c6-d6b3b2718de2 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.629454Z

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Observation c07874be-d5ea-4675-828d-fef10424f5d8 · outbound

This paper cites Train short, test long: Attention with linear biases enables input length extrapolation.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Train short, test long: Attention with linear biases enables input length extrapolation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.633171Z

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Observation 578f4abc-5d32-4ca5-9a6a-225391d7a950 · outbound

This paper cites A length-extrapolatable transformer.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning A length-extrapolatable transformer

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.602633Z

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Observation ab4703f0-dd1b-405a-890e-650818553752 · outbound

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

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.026713Z

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Observation f8650ce2-953d-4d40-8b58-a194e8ede038 · outbound

This paper cites Qwen Technical Report.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Qwen Technical Report

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:24.906276Z

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Observation db7bad15-753f-490c-af63-514c779360a4 · outbound

This paper cites Extending Context Window of Large Language Models via Positional Interpolation.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Extending Context Window of Large Language Models via Positional Interpolation

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:24.987256Z

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Observation 4a40b6cf-fac3-47bc-8bb4-971fdab2540b · outbound

This paper cites Ntk-aware scaled rope allows llama models to have extended(8k+) context size without any fine-tuning and minimal perplexity degradation.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Ntk-aware scaled rope allows llama models to have extended(8k+) context size without any fine-tuning and minimal perplexity degradation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.621758Z

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Observation a9cc0e3d-7a8b-4690-bf0a-cb1ecb43c6d0 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning YaRN: Efficient Context Window Extension of Large Language Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.037306Z

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Observation ce834180-76a6-4d48-a7cd-21db64076b08 · outbound

This paper cites Efficient streaming language models with attention sinks.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Efficient streaming language models with attention sinks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.606464Z

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Observation 4a0fba67-58c7-4b60-b080-41ad7d73cd8a · outbound

This paper cites Dynamic context pruning for efficient and interpretable autoregressive transformers.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Dynamic context pruning for efficient and interpretable autoregressive transformers

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.613942Z

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Observation f266c08e-13e5-49ad-92b3-cc4fa45f6c38 · outbound

This paper cites Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.982446Z

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Observation 7dba45d0-6038-4f15-93df-6c2cede87840 · outbound

This paper cites Lm-infinite: Zero-shot extreme length generalization for large language models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Lm-infinite: Zero-shot extreme length generalization for large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.673492Z

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Observation c18f7381-5317-4451-827a-95df074e1685 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Lora: Low-rank adaptation of large language models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.595202Z

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Observation 472abfa2-b7c0-49ee-b743-44f46bab77c1 · outbound

This paper cites LLoCO: Learning Long Contexts Offline.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning LLoCO: Learning Long Contexts Offline

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:25.032197Z

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Observation e863f0b8-a670-4ee6-b912-5633b7586610 · outbound

This paper cites Unlocking Context Constraints of LLMs: Enhancing Context Efficiency of LLMs with Self-Information-Based Content Filtering.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Unlocking Context Constraints of LLMs: Enhancing Context Efficiency of LLMs with Self-Information-Based Content Filtering

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:25.022655Z

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Observation d797e297-781b-46e5-b9c0-620dbff3f488 · outbound

This paper cites LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:25.007623Z

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Observation 6e3d49da-e6f5-4212-9898-4973aa518ed9 · outbound

This paper cites Learning to compress prompts with gist tokens.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Learning to compress prompts with gist tokens

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.677290Z

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Observation 1f0f81a9-5e48-4566-bcdb-a934b7060319 · outbound

This paper cites In-context Autoencoder for Context Compression in a Large Language Model.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning In-context Autoencoder for Context Compression in a Large Language Model

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.998229Z

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Observation c9237e63-ae52-4224-af85-ee653d651897 · outbound

This paper cites Adapting language models to compress contexts.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Adapting language models to compress contexts

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.636622Z

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Observation 8ffb0955-90e2-4206-8a82-76fafce9e37c · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.067901Z

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Observation 9db04a62-3ea9-423c-aa1f-40a01979516c · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning C-Pack: Packed Resources For General Chinese Embeddings

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.017231Z

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Observation 4ae2913b-bc48-4ef1-a751-f07098c957f2 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Gaussian Error Linear Units (GELUs)

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.002470Z

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Observation 6bc17e03-2356-416f-8c0d-2c48996c7561 · outbound

This paper cites Vision-language models for vision tasks: A survey.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Vision-language models for vision tasks: A survey

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.680894Z

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Observation 940e4293-a78e-453b-95b2-c152dd1b7d1b · outbound

This paper cites Minigpt-4: Enhancing vision-language understanding with advanced large language models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Minigpt-4: Enhancing vision-language understanding with advanced large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.665896Z

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Observation a1ffd719-f9ff-4d79-9a30-3265fd1b2ab3 · outbound

This paper cites Visual instruction tuning.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Visual instruction tuning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.669619Z

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Observation 82fafbbf-0b9b-4f52-9ad5-1145c87930fd · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.048063Z

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Observation 1a53d616-e58d-4edc-8650-338ab5181d84 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.661857Z

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Observation 5e7449ec-9a83-4724-a87d-d617d0cede6f · outbound

This paper cites A Survey on Optical Character Recognition System.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning A Survey on Optical Character Recognition System

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:25.012575Z

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Observation ebffff64-8a37-4aae-834d-1ee0942722d6 · outbound

This paper cites Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:25.058662Z

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Observation 014316c1-918e-4072-b2f1-d50766f9bcd3 · outbound

This paper cites LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.960782Z

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Observation 47e80560-7b26-492f-8af7-60891cbb40bf · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:38:24.977189Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c77e759f-6422-4247-b310-ad34e526bae8 · outbound

This paper cites QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:24.992490Z

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Observation e869470e-7080-46c3-a2c9-c4d0a4a9e16d · outbound

This paper cites Efficient attentions for long document summarization.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Efficient attentions for long document summarization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.654599Z

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Observation 519401d4-97fd-41a0-8a31-e816e6ebd6d8 · outbound

This paper cites Quality: Question answering with long input texts, yes! NAACL 2022.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Quality: Question answering with long input texts, yes! NAACL 2022

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.658090Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fd2a6afb-2491-49cd-a68b-0997bc86faf8 · outbound

This paper cites The NarrativeQA reading comprehension challenge.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning The NarrativeQA reading comprehension challenge

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.598966Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aa9e0347-9d84-44e0-9eef-a0bc44a5af64 · outbound

This paper cites Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.610254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ecb34b06-649b-4d69-b8e5-81ef9adb58ba · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Rouge: A package for automatic evaluation of summaries

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.588253Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e7cbb6d9-bbe7-4f38-a59d-4de40686d9dd · outbound

This paper cites Zeroscrolls: A zero-shot benchmark for long text understanding.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Zeroscrolls: A zero-shot benchmark for long text understanding

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:38:25.651352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 897680a3-9165-4a76-8e82-e94ca4b7bf60 · outbound

This paper cites How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:38:25.053129Z

Source-reported events for the cited work

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This paper cites Context Embeddings for Efficient Answer Generation in RAG.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Context Embeddings for Efficient Answer Generation in RAG

Reference 50

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