Papers with system architecture

14 papers
A Multilingual Reading Comprehension System for more than 100 Languages (2020.coling-demos)

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Challenge: Recent advances in open domain question answering (QA) have focused on machine reading comprehension (MRC)
Approach: They propose a multilingual machine reading comprehension (MRC) demo which can answer questions in over 100 languages.
Outcome: The proposed system can answer questions in over 100 languages and integrates with IBM Watson's machine translation widget to improve language accessibility.
AutoForest: Automatically Generating Forest Plots from Biomedical Studies with End-to-End Evidence Extraction and Synthesis (2026.acl-demo)

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Challenge: Existing systems that generate publication-ready forest plots from biomedical papers are fragmented and time-consuming.
Approach: They propose a system that generates publication-ready forest plots directly from biomedical papers . autoforest automatically suggests ICO elements, extracts outcome data and performs statistical synthesis . authors demonstrate how the system can accelerate evidence synthesis and lower the barrier to conducting meta-analyses .
Outcome: The proposed system accelerates evidence synthesis and lowers the barrier to meta-analyses.
Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support (2025.emnlp-demos)

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Challenge: Existing systems that provide contextually relevant information are difficult to deploy in a university setting . a number of universities are developing or using chatbots to support prospective students .
Approach: They propose a conversational agent called Marcel that uses retrieval-augmented generation to provide contextually relevant information.
Outcome: The proposed system is designed to provide fast and personalized responses while reducing workload.
Sounding Board: A User-Centric and Content-Driven Social Chatbot (N18-5)

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Challenge: Sounding Board is a social chatbot that can hold a coherent conversation with humans . the system is user-centric in that users can control the topic of conversation, while the system adapts to the user's needs.
Approach: They present Sounding Board, a social chatbot that won the 2017 Amazon Alexa Prize.
Outcome: The system is user-centric in that users can control the topic of conversation, while the system adapts to the user's needs.
Visualizing Inferred Morphotactic Systems (N19-4)

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Challenge: a web-based system facilitates the exploration of complex morphological patterns found in morphology rich languages.
Approach: They propose a web-based system that facilitates the exploration of complex morphological patterns found in morphology rich languages.
Outcome: The proposed system can be used to explore morphological patterns in morphology rich languages.
GovScape: A Public Multimodal Search System for 70 Million Pages of Government PDFs (2026.acl-demo)

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Challenge: Efforts over the past three decades have produced web archives containing billions of webpage snapshots and petabytes of data.
Approach: They propose a public search system that supports multimodal searches across 10,015,993 federal government PDFs from the 2020 End of Term crawl.
Outcome: The proposed system supports multimodal searches across 10,015,993 federal government PDFs from the 2020 End of Term crawl (70,958,487 total PDF pages) significant compute cost for GovScape’s pre-processing pipeline for 10 million PDFs was approximately 1,500, equivalent to 47,000 PDF pages per dollar spent on compute.
Speakerly: A Voice-based Writing Assistant for Text Composition (2023.emnlp-industry)

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Challenge: Speakerly TM is a voice-based writing assistance system that works across the different stages of writing.
Approach: They propose a voice-based writing assistance system that helps users with text composition across various use cases such as emails, instant messages, and notes.
Outcome: The proposed system can be used for email, instant messages, and notes.
Zero-shot Slot Filling in the Age of LLMs for Dialogue Systems (2025.coling-industry)

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Challenge: Existing methods for zero-shot slot filling focus on text data, overlooking conversational data.
Approach: They propose a method for automatic data annotation with slot induction and black-box knowledge distillation from a teacher LLM to a smaller model.
Outcome: The proposed method outperforms existing models on internal datasets by 26% relative increase in F1 score.
Compact Personalized Models for Neural Machine Translation (D18-1)

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Challenge: a large proportion of model parameters can be frozen during adaptation with minimal or no reduction in translation quality.
Approach: They propose gradient-based domain adaptation methods for self-attentive machine translation models . they encourage structured sparsity in the set of offset tensors during learning .
Outcome: The proposed method achieves high space and time efficiency using sparse models . the results compare the proposed method with incremental adaptation .
Automatic Text Simplification for Social Good: Progress and Challenges (2021.findings-acl)

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Challenge: ATS has been promoted as a natural language processing task since the 1990s . but since 2010, the field has been focusing on building complex end-to-end neural architectures based on ATS .
Approach: They propose to use automated text simplification (ATS) to make texts more accessible to people with disabilities . they argue that lack of high-quality TS datasets and standardized evaluation procedures are barriers .
Outcome: The proposed neural ATS systems are based on a new set of TS datasets and a standardized evaluation procedure.
DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages (2022.emnlp-main)

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Challenge: Recent advances in neural language modeling and multilingual training have prompted widespread adoption of machine translation (MT) technologies across an unprecedented range of world languages.
Approach: They propose to use a dataset to assess the impact of two state-of-the-art NMT systems, Google Translate and the multilingual mBART-50 model, on translation productivity.
Outcome: The proposed model is faster than translation from scratch, but the magnitude of productivity gains varies widely across systems and languages.
Language (Re)modelling: Towards Embodied Language Understanding (2020.acl-main)

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Challenge: Despite the rapid progress in NLU, current systems lack the rich mental representations that people use for language understanding.
Approach: They propose an approach to representation and learning based on the tenets of embodied cognitive linguistics (ECL) they propose a system architecture along with a roadmap towards realizing this vision.
Outcome: The proposed approach will improve the performance of existing systems and provide a roadmap towards realizing this vision.
Context-Aware Document Simplification (2023.findings-acl)

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Challenge: Recent work on document simplification has focused on sentence-level inputs but fails to preserve the discourse structure.
Approach: They explore various systems that use document context within the simplification process . they investigate the performance and efficiency tradeoffs of system variants .
Outcome: The proposed approach achieves state-of-the-art even when not relying on plan-guidance.
Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework (2026.acl-long)

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Challenge: Recent advances in large language models have demonstrated strong potential for understanding user intent . paper describes system architecture, agent roles, retrieval and scoring methods, knowledge graph schema, and evaluation interfaces .
Approach: They propose a multi-agent research discovery and analysis system that integrates multiple agents to reduce the effort required to find, assess, organize, and understand academic literature.
Outcome: The proposed system reduces the effort required to find, assess, organize, and understand academic literature.

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