Papers with unified pipeline
Stakeholder Suite: A Unified AI Framework for Mapping Actors, Topics and Arguments in Public Debates (2026.eacl-demo)
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| Challenge: | Existing media intelligence tools rely on descriptive analytics with limited transparency. |
| Approach: | They propose a framework for mapping actors, topics, and arguments within public debates . it combines actor detection, topic modeling, argument extraction and stance classification . the framework is tested on multiple energy infrastructure projects as a case study . |
| Outcome: | The proposed framework delivers fine-grained, source-grounded insights while remaining adaptable to diverse domains. |
PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models (2024.acl-long)
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Haoran Li, Dadi Guo, Donghao Li, Wei Fan, Qi Hu, Xin Liu, Chunkit Chan, Duanyi Yao, Yuan Yao, Yangqiu Song
| Challenge: | generative large language models (LLMs) exhibit surprising capability and integrate previous tasks into a unified text generation formulation. |
| Approach: | They propose a privacy evaluation benchmark to quantify the privacy leakage of language models. |
| Outcome: | The proposed benchmark compares PPLMs with different privacy implementations to find out how privacy leakage is handled. |
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation (2026.acl-demo)
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Abdelrahman Abdallah, Bhawna Piryani, Jamshid Mozafari, Andreas Herzinger, Jamie Holdcroft, Adam Jatowt
| Challenge: | Rankify unifies retrieval-augmented generation (RAG) and retrieval based question answering systems. |
| Approach: | They propose an open-source Python toolkit that unifies retrieval-augmented generation in a single modular framework. |
| Outcome: | The proposed framework unifies retrieval-augmented generation (RAG) tools in a single modular framework. |
CLTR: An End-to-End, Transformer-Based System for Cell-Level Table Retrieval and Table Question Answering (2021.acl-demo)
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| Challenge: | Existing systems that retrieve tables based on keyword queries and table contents often result in poor quality . a growing demand for natural language questions over tables to be used for QA . |
| Approach: | They propose an end-to-end transformer-based table question answering system that takes natural language questions and massive table corpora as inputs to retrieve the most relevant tables. |
| Outcome: | The proposed system can retrieve relevant tables and locate the correct cells to answer questions. |
Trove: A Flexible Toolkit for Dense Retrieval (2026.eacl-demo)
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| Challenge: | Existing retrieval tools require considerable engineering effort for many tasks like efficient data management or model customization. |
| Approach: | They propose a novel open-source retrieval toolkit that simplifies research experiments without sacrificing flexibility or speed. |
| Outcome: | The proposed tool reduces memory consumption by 2.6 and allows for arbitrary customizations. |
More Data or Better Data? A Critical Analysis of Data Selection and Synthesis for Mathematical Reasoning (2025.emnlp-industry)
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| Challenge: | Despite various proposed data construction methods, their practical utility in real-world pipelines remains underexplored. |
| Approach: | They conduct a comprehensive analysis of open-source datasets and data synthesis techniques for mathematical reasoning under a unified pipeline designed to mirror training and deployment scenarios. |
| Outcome: | The proposed pipelines mirror training and deployment scenarios and are suitable for industrial applications. |
Interpretability Analysis of Arithmetic In-Context Learning in Large Language Models (2025.emnlp-main)
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| Challenge: | Large language models (LLMs) solve arithmetic with only a few in-context examples, yet the computations that connect those examples to the answer remain opaque. |
| Approach: | They propose to use in-context examples to illustrate how large language models process ICEs to isolate partial-sum representations in three-operand tasks and investigate their influence on final logits. |
| Outcome: | The proposed model performs better than previous models on three-operand tasks. |
Text2Mem: A Unified Memory Operation Language for Memory Operating System (2026.findings-acl)
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| Challenge: | Existing memory frameworks lack a formal, executable specification for memory control. |
| Approach: | They propose a unified memory operation language that standardizes translation of natural-language instructions into reliable execution. |
| Outcome: | The proposed language standardizes translation of natural-language instructions into reliable execution. |
Frame First, Then Extract: A Frame-Semantic Reasoning Pipeline for Zero-Shot Relation Triplet Extraction (2025.emnlp-main)
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| Challenge: | Existing methods to extract triplets for unseen relations rely on costly fine-tuning and lack structured semantic guidance. |
| Approach: | They propose a framework that adopts a "frame first, then extract" paradigm to extract triplets from unstructured text. |
| Outcome: | The proposed framework achieves competitive zero-shot performance on multiple benchmarks and can be used to enhance existing extraction methods. |
RACCooN: Versatile Instructional Video Editing with Auto-Generated Narratives (2025.emnlp-main)
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| Challenge: | Recent video generative models rely on detailed, labor-intensive text prompts for tasks, limiting adaptability for personal/raw videos. |
| Approach: | They propose a video-to-paragraph-to video editing method that supports diverse video editing capabilities, such as removal, addition, and modification, through a unified pipeline. |
| Outcome: | The proposed method supports diverse video editing capabilities, such as removal, addition, and modification, through a unified pipeline. |