Papers with BC
Probing the Multi-turn Planning Capabilities of LLMs via 20 Question Games (2024.acl-long)
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| Challenge: | Large language models (LLMs) are effective at answering clear questions but when faced with ambiguous queries they act unpredictably and produce incorrect outputs. |
| Approach: | They propose to use a surrogate problem to assess an LLMs’s ability to deduce an entity unknown to itself, but revealed to a judge, by asking the judge a series of queries. |
| Outcome: | The proposed model outperforms human players on the entity-deducing task by a large margin. |
BPM_MT: Enhanced Backchannel Prediction Model using Multi-Task Learning (2021.emnlp-main)
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| Challenge: | Backchannel (BC) is a short and quick reaction signal of a listener to a speaker's utterances. |
| Approach: | They propose a model that utilizes lexical information in utterances to enhance backchannel (BC) prediction. |
| Outcome: | The proposed model showed 14.24% performance improvement compared to baseline in the four BC categories: continuer, understanding, empathic response, and No BC. |
Eliciting Motivational Interviewing Skill Codes in Psychotherapy with LLMs: A Bilingual Dataset and Analytical Study (2024.lrec-main)
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Xin Sun, Jiahuan Pei, Jan de Wit, Mohammad Aliannejadi, Emiel Krahmer, Jos T.P. Dobber, Jos A. Bosch
| Challenge: | Motivational interviewing (MI) is an essential, directive, client-centered counseling technique. |
| Approach: | They propose a bilingual dataset of MI conversations in English and Dutch . they propose an approach to elicit MISC expertise from Large language models . |
| Outcome: | The proposed approach yields results aligned with expert annotations and maintains consistent performance across languages. |
Ancient Chinese Glyph Identification Powered by Radical Semantics (2024.findings-acl)
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| Challenge: | Currently, about half of ancient Chinese glyphs have not been deciphered yet. |
| Approach: | They propose to use a Chinese glyph knowledge graph to infer the Chinese character label for the unknown ancient Chinese . they propose to combine the visual, textual, and the graph data to create a multimodal Chinese morph identification framework. |
| Outcome: | The proposed method can identify ancient Chinese characters from 1300 BC to 200 BC based on image and radical semantics on a 1000-year-old Chinese glyph dataset. |
Minimal Yet Big Impact: How AI Agent Back-channeling Enhances Conversational Engagement through Conversation Persistence and Context Richness (2024.findings-emnlp)
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| Challenge: | Increasing use of AI agents in conversational services highlights the importance of back-channeling (BC) as an active listening strategy to enhance conversational engagement. |
| Approach: | They conducted an experiment with 55 participants to evaluate conversational engagement using both quantitative and qualitative metrics. |
| Outcome: | The results show that the Todak_BC and TodAK_NoBC groups have significantly higher conversational engagement than the Todask_NoB. |
MM-JudgeBias: A Benchmark for Evaluating Compositional Biases in MLLM-as-a-Judge (2026.acl-long)
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| Challenge: | Multimodal Large Language Models (MLLMs) are increasingly used as automatic judges . however, their reliability and vulnerabilities to biases remain underexplored . |
| Approach: | They propose a benchmark to evaluate MLLMs that fail to integrate visual cues . they also introduce a test to evaluate the reliability of MLMLs based on a set of asymmetric evaluation tendencies. |
| Outcome: | Experiments on 26 state-of-the-art MLLMs reveal modality neglect and asymmetric evaluation tendencies . a standardized model with a benchmark enables a fine-grained diagnosis of nine bias types . |