LAB SEMINAR/WORKSHOP

SUMMER SEMINAR

DATE SUBJECT PRESENTER MATERIALS
07.04 Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module Operation Jung, Dahyun link
Machine Unlearning of Pre-trained Large Language Models
Fine-Tuning Language Models For Factuality Kang, Myunghoon link
Assessing Factual Reliability of Large Language Model Knowledge
Language models can explain neurons in language models Chun, Yong Chan link
Sparse autoencoders find highly interpretable features in large language model
07.11 QLLM: ACCURATE AND EFFICIENT LOW-BITWIDTH QUANTIZATION FOR LARGE LANGUAGE MODELS Lim, Jungwoo link
OMNIQUANT: OMNIDIRECTIONALLY CALIBRATED QUANTIZATION FOR LARGE LANGUAGE MODELS
INSIDE: LLMS’ INTERNAL STATES RETAIN THE POWER OF HALLUCINATION DETECTION Seo, Jaehyung link
On Large Language Models’ Hallucination with Regard to Known Facts
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems Park, Chanhee link
LLM Comparative Assessment Zero-shot NLG Evaluation through Pairwise Comparisons using Large Language Models

WINTER SEMINAR

DATE SUBJECT PRESENTER MATERIALS
01.04 ALCUNA: Large Language Models Meet New Knowledge Lee, Jungseob link
Large Language Models Can Self-Improve
Evaluating Large Language Models At Evaluating Instruction Following Moon, Hyeonseok link
Human Feedback is not Gold Standard
Language Representation Projection: Can We Transfer Factual Knowledge across Languages in Multilingual Language Models? Hong, Seongtae link
SoulChat: Improving LLMs’ Empathy, Listening, and Comfort Abilities through Fine-tuning with Multi-turn Empathy Conversations
01.11 Inference-Time Intervention: Eliciting Truthful Answers from a Language Model Jung, Dahyun link
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation
Hallucination Mitigation in Natural Language Generation from Large-Scale Open-Domain Knowledge Graphs Seo, Jaehyung link
The Troubling Emergence of Hallucination in Large Language Models – An Extensive Definition, Quantification, and Prescriptive Remediations
Unveiling the Pitfalls of Knowledge Editing for Large Language Models Son, Junyoung link
RA-DIT: Retrieval-Augmented Dual Instruction Tuning
01.19 Emergent and Predictable Memorization in Large Language Models Lim, Jungwoo link
ProPILE: Probing Privacy Leakage in Large Language Models
CESAR: Automatic Induction of Compositional Instructions for Multi-turn Dialogs Koo, Seonmin link
SELF-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations
02.01 The case for 4-bit precision: k-bit Inference Scaling Laws Lee, Jaewook link
LLM-FP4: 4-Bit Floating-Point Quantized Transformers
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators Kang, Myunghoon link
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
Direct Preference Optimization: Your Language Model is Secretly a Reward Model Kim, Jeongwook link
Mixtral of Experts
02.22 Prompting is not a substitute for probability measurements in large language models Kim, Jinsung link
Evaluating Large Language Models on Controlled Generation Tasks
Knowledge-enhanced mixed-initiative dialogue system for emotional support conversations Son, Suhyune link
Enhancing Empathetic and Emotion Support Dialogue Generation with Prophetic Commonsense Inference
02.29 Bridging the Digital Divide: Performance Variation across Socio-Economic Factors in Vision-Language Models Lee, Seungyoon link
Merging Generated and Retrieved Knowledge for Open-Domain QA
MoLE: Mixture of LoRA Experts Eo, Sugyeong link
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models
DYNOSAUR: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation Jang, Yoonna link
Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration

SUMMER SEMINAR

DATE SUBJECT PRESENTER MATERIALS COMMENTS
08.03 Think-on-Graph: Deep and Responsible Reasoning of Large Language Model with Knowledge Graph Son, Suhyune link
Chain of Knowledge: A Framework for Grounding Large Language Models with Structured Knowledge Bases
Rethinking with Retrieval: Faithful Large Language Model Inference
How Language Model Hallucinations Can Snowball Eo, Sugyeong link
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
Detoxifying Text with MARCO: Controllable Revision with Experts and Anti-Experts
Generate rather than Retrieve: Large Language Models are Strong Context Generators Lee, Seungyoon link
Guess The Instruction! Flipped Learning Makes Language Models Strong Zero-Shot Learners
Leveraging Large Language Models For Multiple Choice Question Answering
08.10 SELF-INSTRUCT: Aligning Language Models with Self-Generated Instructions Lee, Jeongwoo link
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Large Language Models Can Self-Improve
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models Kim, Jeongwook link
ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning Moon, Hyeonseok link
PARAMETER-EFFICIENT FINE-TUNING DESIGN SPACES
Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Models
08.18 Linearly Mapping from Image to Text Space Lee, Jungseob link
MAGMA – Multimodal Augmentation of Generative Models through Adapter-based Finetuning
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models
Visual Instruction Tuning
LLaMA2: Open and Efficient Foundation Language Models Lee, Seungjun link
FLAN
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering Lee, Jaewook link
Enhanced Story Comprehension for Large Language Models through Dynamic Document-Based Knowledge Graphs
ChatDB: Augmenting LLMs With Databases as Their Symbolic Memory
08.24 LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention Hong, Seongtae link
LLAMA-Adapter. V2:
LIMA: Less Is More for Alignment
Plug-and-Play Knowledge Injection for Pre-trained Language Models Jung, Dahyun link
Towards Continual Knowledge Learning of Language Models
Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models Lim, Jungwoo link
Mitigating Language Model Hallucination with Interactive Question-Knowledge Alignment
PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions
08.31 fireball: a dataset of dungeons and dragons actual-play with structured game state information Kim, Jinsung link comments
marked personas: using natural language prompts to measure stereotypes in language models
What, When, and How to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue
 Automatic Chain of Thought Prompting in Large Language Models Son, Junyoung link
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
Zero-shot Faithful Factual Error Correction Kang, Myunghoon link
SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
Language Models (Mostly) Know What They Know
09.07 HellaSwag: Can a Machine Really Finish Your Sentence? Seo, Jaehyung link comments
Measuring Massive Multitask Language Understanding
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge (ARC)
TruthfulQA: Measuring How Models Mimic Human Falsehoods
Clues Before Answers: Generation-Enhanced Multiple-Choice QA Koo, Seonmin link
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledge
LoRA: Low-Rank Adaptation of Large Language Models Jang, Yoonna link
Stack More Layers Differently: High-Rank Training Through Low-Rank Updates
LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

WINTER SEMINAR

DATE SUBJECT PRESENTER MATERIALS
01.26 RankGen: Improving Text Generation with Large Ranking Models Lim, Jungwoo link
Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination
Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space
Generative Language Models for Paragraph-Level Question Generation Kang, Myunghoon link
Varifocal Question Generation for Fact-checking
Generating Literal and Implied Subquestions to Fact-check Complex Claims
02.02 Detecting Label Erros by using Pre-trained Langauge Model Lee, Seungjun link
Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition
Break it Down into BTS: Basic, Tiniest Subword Units for Korean
SALTED: A Framework for SAlient Long-tail Translation Error Detection Eo, Sugyeong link
CTRLsum: Towards Generic Controllable Text Summarization
SentBS: Sentence-level Beam Search for Controllable Summarization
02.09 AMAL:Meta Knowledge-Driven Few-Shot Adapter Learning Kim, Jinsung link
Dictionary-Assisted Supervised Contrastive Learning
Fast Vocabulary Transfer for Language Model Compression
Revisiting Parameter-Efficient Tuning: Are We Really There Yet? Moon, Hyeonseok link
Evaluating Parameter Efficient Learning for Generation
An Empirical Study on the Transferability of Transformer Modules in Parameter-Efficient Fine-Tuning
02.16 Entity-centered Cross-document Relation Extraction Son, Junyoung link
DocInfer: Document-level Natural Language Inference using Optimal Evidence Selection
Entity Extraction in Low Resource Domains with Selective Pre-training of Large Language Models