Papers with real-life scenarios
SELF-PERCEPT: Introspection Improves Large Language Models’ Detection of Multi-Person Mental Manipulation in Conversations (2025.acl-short)
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Danush Khanna, Pratinav Seth, Sidhaarth Sredharan Murali, Aditya Kumar Guru, Siddharth Shukla, Tanuj Tyagi, Sandeep Chaurasia, Kripabandhu Ghosh
| Challenge: | Mental manipulation is subtle yet pervasive form of abuse in interpersonal communication, making its detection critical for safeguarding potential victims. |
| Approach: | They propose a dataset of 220 multi-turn, multi-person dialogues balanced between manipulative and non-manipulative interactions drawn from reality shows that mimic real-life scenarios. |
| Outcome: | The proposed framework shows that it can detect multi-person, multi-turn mental manipulation in multi-people conversations. |
COMPKE: Complex Question Answering under Knowledge Editing (2025.findings-acl)
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| Challenge: | Existing benchmarks for knowledge editing do not accurately evaluate how well models apply knowledge in real-life situations. |
| Approach: | They propose a benchmark to evaluate how well updated models apply new knowledge in real-life situations. |
| Outcome: | The proposed method achieves 39.47 accuracy on GPT-4o-mini but drops significantly to 3.83 on Qwen2.5-3B. |
Rethinking Task-Oriented Dialogue Systems: From Complex Modularity to Zero-Shot Autonomous Agent (2024.acl-long)
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| Challenge: | Task-oriented dialogue systems are designed to be composed of several functional modules, but lacks a general-purpose instruction-following language model. |
| Approach: | They propose a fully zero-shot autonomous TOD agent that leverages a general-purpose instruction-following language model to decide what to do at each dialogue turn. |
| Outcome: | The proposed agent can perform tasks in real-life scenarios with a general-purpose instruction-following language model. |
A Multifaceted Framework to Evaluate Evasion, Content Preservation, and Misattribution in Authorship Obfuscation Techniques (2022.emnlp-main)
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| Challenge: | Authorship obfuscation techniques are often evaluated based on their ability to hide the author’s identity (evasion) while preserving the content of the original text. |
| Approach: | They propose to evaluate authorship obfuscation techniques on detection evasion and content preservation using competitive identification techniques in real-life scenarios. |
| Outcome: | The proposed method reveals key weaknesses in state-of-the-art obfuscation techniques and surprisingly competitive effectiveness from a back-translation baseline in all evaluation aspects. |
SafeText: A Benchmark for Exploring Physical Safety in Language Models (2022.emnlp-main)
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Sharon Levy, Emily Allaway, Melanie Subbiah, Lydia Chilton, Desmond Patton, Kathleen McKeown, William Yang Wang
| Challenge: | Existing models that generate unsafe text are susceptible to the dangers of unsafe text generation and are deemed unsafe. |
| Approach: | They use a dataset to empirically study commonsense physical safety across various models for text generation and reasoning tasks. |
| Outcome: | The proposed model can generate unsafe text and reject it, but the different harms that can occur do not receive equal attention, which may consequently downplay certain harms. |
CLEEK: A Chinese Long-text Corpus for Entity Linking (2020.lrec-1)
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| Challenge: | Entity linking is a fundamental task in natural language processing, says nigel kilgstrom . existing corpora for entity linking in china are lacking and deficient, he says . kilsmstrom: a new method for entity disambiguation can be developed for Chinese . |
| Approach: | They build a Chinese corpus of multi-domain long text for entity linking . they evaluate the difficulty of documents with respect to entity linking using a measure . |
| Outcome: | The proposed corpus is based on 100 documents from diverse domains and is publicly accessible. |
MetaLogic: Logical Reasoning Explanations with Fine-Grained Structure (2022.emnlp-main)
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| Challenge: | Current explanation datasets often employ synthetic data with simple reasoning structures. |
| Approach: | They propose a comprehensive logical reasoning explanation form that incorporates three main components to better fit the human cognitive process. |
| Outcome: | The proposed model performs better than existing models on real-life scenarios, but is more challenging for the current models. |
Faux Polyglot: A Study on Information Disparity in Multilingual Large Language Models (2025.naacl-long)
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| Challenge: | Recent surge in multilingual large language models (LLMs) and Retrieval Augmented Generation (RAG) has significantly expanded conversational search across varied linguistic and cultural demographics. |
| Approach: | They found that LLMs displayed systemic bias towards information in the same language as query language in document retrieval and answer generation. |
| Outcome: | The results highlight the linguistic divide within multilingual LLMs in information search systems. |
End-to-End Single-Channel Speaker-Turn Aware Conversational Speech Translation (2023.emnlp-main)
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Juan Pablo Zuluaga-Gomez, Zhaocheng Huang, Xing Niu, Rohit Paturi, Sundararajan Srinivasan, Prashant Mathur, Brian Thompson, Marcello Federico
| Challenge: | Conventional speech-to-text translation systems are trained on single-speaker utterances, but they may not be applicable to real-life scenarios where the audio contains conversations by multiple speakers. |
| Approach: | They propose a speaker-turn-aware conversational speech translation model that integrates automatic speech recognition, speech translation and speaker turn detection using special tokens in a serialized labeling format. |
| Outcome: | The proposed model outperforms the reference systems on the multi-speaker condition while attaining comparable performance on the single-speakspeaker conditions. |
Exploring In-Context Learning for Knowledge Grounded Dialog Generation (2023.findings-emnlp)
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| Challenge: | Existing knowledge grounded dialog generation models are prone to hallucination and produce factually inaccurate outputs. |
| Approach: | They propose a retrieval-based framework which leverages in-context learning and retrieval techniques to enhance LLMs on knowledge grounded dialog generation. |
| Outcome: | The proposed framework outperforms existing training-based models on a large-scale knowledge graph with 1M+ facts and is expected to perform knowledge-intensive tasks. |
Re-Examine Distantly Supervised NER: A New Benchmark and a Simple Approach (2025.coling-main)
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| Challenge: | Existing DS-NER approaches rely on large validation sets and test set for tuning inappropriately. |
| Approach: | They propose a method where training data is annotated using domain dictionaries and test data is analyzed by domain experts. |
| Outcome: | The proposed method reduces the need for labor-intensive manual annotations but rely on large human labeled validation set. |
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations (2023.findings-emnlp)
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Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, Yejin Choi
| Challenge: | Moral or ethical judgments rely heavily on the contexts in which they occur . a student model that produces defeasible contexts with improved validity, diversity, and defasibility is superior to intermediate student models . |
| Approach: | a new study uses a student model to provide contextualizations that make an action morally acceptable . the model is based on a dataset of 115K defeasible moral actions rated highly by human annotators . |
| Outcome: | The proposed model outperforms all intermediate models in a high-quality dataset . the model is based on 1.2M entries of contextualizations and rationales for 115K moral actions . |
CToolEval: A Chinese Benchmark for LLM-Powered Agent Evaluation in Real-World API Interactions (2024.findings-acl)
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| Challenge: | a benchmark is designed to evaluate the capabilities of large language models (LLMs) as agents in decision making and operational tasks. |
| Approach: | They propose a benchmark to evaluate LLMs in the context of Chinese societal applications . they propose he benchmark will evaluate tool invocation ability of LLM and task completion ability . |
| Outcome: | The proposed benchmark features 398 APIs across 27 widely-used Apps across 14 domains. |
Fair Text Classification with Wasserstein Independence (2023.emnlp-main)
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| Challenge: | a novel method for mitigating group fairness in text classification remains an open challenge . a recent paper focuses on the problem of group fair in the domain of natural language processing . |
| Approach: | They propose a method for mitigating group fairness in neural text classification . they use adversarial training to induce Wasserstein independence between representations . |
| Outcome: | The proposed method exhibits a comparable or better fairness-accuracy trade-off compared to existing methods. |