| Challenge: | Existing methods for text stream modeling ignore fine-grained timing irregularities and time-varying scale-free properties of texts. |
| Approach: | They propose a hyperbolic Hawkes Attention Network which learns a data-driven hyperbolical space and models irregular powerlaw excitations using a Hawke's process. |
| Outcome: | The proposed model can model online text sequences in a geometry agnostic manner. |
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| Challenge: | Recent studies have shown that LLM-based EHR question answering is costly to deploy and does not leverage hierarchical structure of clinical data. |
| Approach: | They propose a Lorentzian model that embeds codes, visits, and questions in hyperbolic space and answers queries via geometry-consistent cross-attention with type-specific pointer heads. |
| Outcome: | The proposed model embeds codes, visits, and questions in hyperbolic space and answers queries via geometry-consistent cross-attention with type-specific pointer heads. |
From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons (2026.acl-long)
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| Challenge: | Autoregressive (AR) models rely on bidirectional attention, creating a structural mismatch with pre-trained Autoregression models. |
| Approach: | They propose a framework that efficiently adapts autoregressive (AR) models to the diffusion paradigm. |
| Outcome: | The proposed framework reduces training costs by orders of magnitude while maintaining state-of-the-art performance. |
Obligation and Prohibition Extraction Using Hierarchical RNNs (P18-2)
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| Challenge: | Existing methods for contract element extraction and contract element classification focus on indicative tokens, but they are not as efficient as the current ones. |
| Approach: | They propose a self-attention mechanism that converts each sentence to an embedding and processes the embeddables to classify each sentence. |
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Exploring Attention Attractors in Large Language Models (2026.acl-long)
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| Challenge: | Existing studies have suggested that attention attractors function as "summary tokens" while others speculate that tokens with weaker semantics attract high attention, they act as attention sinks that offload excessive attention. |
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Every Token Counts: Generalizing 16M Ultra-Long Context in Large Language Models (2026.acl-long)
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| Challenge: | a recent study explores efficient ultra-long context modeling. |
| Approach: | They propose to use Hierarchical Sparse Attention to achieve efficient ultra-long context modeling. |
| Outcome: | The proposed model performs comparable to full-attention baselines on in-domain and out-of-domain tasks. |
SummerTime: Text Summarization Toolkit for Non-experts (2021.emnlp-demo)
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Ansong Ni, Zhangir Azerbayev, Mutethia Mutuma, Troy Feng, Yusen Zhang, Tao Yu, Ahmed Hassan Awadallah, Dragomir Radev
| Challenge: | Recent advances in summarization provide models that can generate high quality summaries . a new toolkit for summarizing text is being developed to make it easier for non-experts to keep track of them. |
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Dynamic and Multi-Channel Graph Convolutional Networks for Aspect-Based Sentiment Analysis (2021.findings-acl)
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| Challenge: | . - (EN) |
| Approach: | . - (EN) |
| Outcome: | . - (EN) |
CLAUSE-ATLAS: A Corpus of Narrative Information to Scale up Computational Literary Analysis (2024.lrec-main)
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| Challenge: | XIX and XX century English novels annotated automatically contain 41,715 labeled clauses . a new approach to analyze novels based on clauses captures structural patterns within books, as well as qualitative differences between them. |
| Approach: | They propose to use a corpus of XIX and XX century English novels annotated automatically to study stories as sequences of eventive, subjective and contextual information. |
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Text Mining for History: first steps on building a large dataset (L18-1)
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| Challenge: | a new corpus on the history domain is being created to mine text in the domain . primary motivation for the project is the need to query the material in a non-linear way . |
| Approach: | They propose to use a Brazilian historical-biographical dictionary as a resource for text mining. |
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Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2023.acl-demo)
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| Challenge: | 58 papers were selected for inclusion in the program, while a small number received only two reviews. |
| Approach: | the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023) will be held in london from July 9-14, 2023 . 58 submissions were selected for inclusion in the program, with an acceptance rate of 37%) |
| Outcome: | the system demonstration track received a record number of submissions . 58 papers were selected for inclusion in the program . |