26 citations · 57 across the 44 of their papers we have counts for
28 papers · 1 filter
DISCO: Distributed Long Context Scaling with Grounding-Reasoning Disaggregation
Guanzheng Chen, Viet Dac Lai, Subhojyoti Mukherjee +5
While Large Language Models (LLMs) advertise million-token context windows, reasoning quality often collapses as inputs grow -- a phenomenon termed context rot. This failure stems…
CHARM: Character Hallucination for Multicultural Role Play Benchmark
Sunkyung Han, Nahyeon Park, Gaeun Seo +2
Role-playing large language models (LLMs) are expected to adopt a character's style while also respecting that character's knowledge boundaries. Prior evaluations detect character…
Code-Switching Reveals Language Anchoring in Multilingual LLMs
Jeonghyun Park, Seunghyun Yoon, Yonghyun Jun +1
Multilingual Large Language Models (MLLMs) are increasingly expected to handle Code-Switched (CS) inputs, yet mixing languages frequently degrades performance relative to source- o…
Instruction Tuning with and without Context: Behavioral Shifts and Downstream Impact
Hyunji Lee, Seunghyun Yoon, Yunjae Won +7
Instruction tuning is a widely used approach to improve the instruction-following ability of large language models (LLMs). Instruction-tuning datasets typically include a mixture o…
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki +6
Offline reinforcement learning (RL) is a variant of RL where the policy is learned from a previously collected dataset of trajectories and rewards. In our work, we propose a practi…
CORG: Generating Answers from Complex, Interrelated Contexts
Hyunji Lee, Franck Dernoncourt, Trung Bui +1
In a real-world corpus, knowledge frequently recurs across documents but often contains inconsistencies due to ambiguous naming, outdated information, or errors, leading to complex…
NoLiMa: Long-Context Evaluation Beyond Literal Matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt +4
Recent large language models (LLMs) support long contexts ranging from 128K to 1M tokens. A popular method for evaluating these capabilities is the needle-in-a-haystack (NIAH) test…
SlimLM: An Efficient Small Language Model for On-Device Document Assistance
Thang M. Pham, Phat T. Nguyen, Seunghyun Yoon +3
While small language models (SLMs) show promises for mobile deployment, their real-world performance and applications on smartphones remains underexplored. We present SlimLM, a ser…
DynaSaur: Large Language Agents Beyond Predefined Actions
Dang Nguyen, Viet Dac Lai, Seunghyun Yoon +9
Existing LLM agent systems typically select actions from a fixed and predefined set at every step. While this approach is effective in closed, narrowly scoped environments, it pres…
KaPQA: Knowledge-Augmented Product Question-Answering
Swetha Eppalapally, Daksh Dangi, Chaithra Bhat +8
Question-answering for domain-specific applications has recently attracted much interest due to the latest advancements in large language models (LLMs). However, accurately assessi…
Identifying Speakers in Dialogue Transcripts: A Text-based Approach Using Pretrained Language Models
Minh Nguyen, Franck Dernoncourt, Seunghyun Yoon +6
We introduce an approach to identifying speaker names in dialogue transcripts, a crucial task for enhancing content accessibility and searchability in digital media archives. Despi…
Towards Enhancing Coherence in Extractive Summarization: Dataset and Experiments with LLMs
Mihir Parmar, Hanieh Deilamsalehy, Franck Dernoncourt +3
Extractive summarization plays a pivotal role in natural language processing due to its wide-range applications in summarizing diverse content efficiently, while also being faithfu…
Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification
Zhongfen Deng, Seunghyun Yoon, Trung Bui +7
Aspect-based meeting transcript summarization aims to produce multiple summaries, each focusing on one aspect of content in a meeting transcript. It is challenging as sentences rel…
Multilingual Sentence-Level Semantic Search using Meta-Distillation Learning
Meryem M'hamdi, Jonathan May, Franck Dernoncourt +2
Multilingual semantic search is the task of retrieving relevant contents to a query expressed in different language combinations. This requires a better semantic understanding of t…
PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioning
Yongil Kim, Yerin Hwang, Hyeongu Yun +3
Vulnerability to lexical perturbation is a critical weakness of automatic evaluation metrics for image captioning. This paper proposes Perturbation Robust Multi-Lingual CLIPScore(P…
Automatic Creation of Named Entity Recognition Datasets by Querying Phrase Representations
Hyunjae Kim, Jaehyo Yoo, Seunghyun Yoon +1
Most weakly supervised named entity recognition (NER) models rely on domain-specific dictionaries provided by experts. This approach is infeasible in many domains where dictionarie…
Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision
Khalil Mrini, Harpreet Singh, Franck Dernoncourt +5
Current medical question answering systems have difficulty processing long, detailed and informally worded questions submitted by patients, called Consumer Health Questions (CHQs).…
PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search
Thang M. Pham, Seunghyun Yoon, Trung Bui +1
While contextualized word embeddings have been a de-facto standard, learning contextualized phrase embeddings is less explored and being hindered by the lack of a human-annotated b…
Fine-grained Image Captioning with CLIP Reward
Jaemin Cho, Seunghyun Yoon, Ajinkya Kale +3
Modern image captioning models are usually trained with text similarity objectives. However, since reference captions in public datasets often describe the most salient common obje…
Factual Error Correction for Abstractive Summaries Using Entity Retrieval
Hwanhee Lee, Cheoneum Park, Seunghyun Yoon +4
Despite the recent advancements in abstractive summarization systems leveraged from large-scale datasets and pre-trained language models, the factual correctness of the summary is…
CAISE: Conversational Agent for Image Search and Editing
Hyounghun Kim, Doo Soon Kim, Seunghyun Yoon +3
Demand for image editing has been increasing as users' desire for expression is also increasing. However, for most users, image editing tools are not easy to use since the tools re…
MACRONYM: A Large-Scale Dataset for Multilingual and Multi-Domain Acronym Extraction
Amir Pouran Ben Veyseh, Nicole Meister, Seunghyun Yoon +3
Acronym extraction is the task of identifying acronyms and their expanded forms in texts that is necessary for various NLP applications. Despite major progress for this task in rec…
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning
Jianguo Zhang, Trung Bui, Seunghyun Yoon +6
In this work, we focus on a more challenging few-shot intent detection scenario where many intents are fine-grained and semantically similar. We present a simple yet effective few-…
QACE: Asking Questions to Evaluate an Image Caption
Hwanhee Lee, Thomas Scialom, Seunghyun Yoon +2
In this paper, we propose QACE, a new metric based on Question Answering for Caption Evaluation. QACE generates questions on the evaluated caption and checks its content by asking…