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Large Language Models

6405 directly classified papers

Papers per year

Papers

From Test-Taking to Test-Making: Examining LLM Authoring of Commonsense Assessment Items EMNLP 2024
Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge EMNLP 2024
AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models NIPS 2024
PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques NIPS 2024
Exploring Context Window of Large Language Models via Decomposed Positional Vectors NIPS 2024
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations NIPS 2024
Saama Technologies at SemEval-2024 Task 2: Three-module System for NLI4CT Enhanced by LLM-generated Intermediate Labels SEMEVAL 2024
Compos Mentis at SemEval2024 Task6: A Multi-Faceted Role-based Large Language Model Ensemble to Detect Hallucination SEMEVAL 2024
NYCU-NLP at SemEval-2024 Task 2: Aggregating Large Language Models in Biomedical Natural Language Inference for Clinical Trials SEMEVAL 2024
Team MLab at SemEval-2024 Task 8: Analyzing Encoder Embeddings for Detecting LLM-generated Text SEMEVAL 2024
Calc-CMU at SemEval-2024 Task 7: Pre-Calc - Learning to Use the Calculator Improves Numeracy in Language Models SEMEVAL 2024
AISPACE at SemEval-2024 task 8: A Class-balanced Soft-voting System for Detecting Multi-generator Machine-generated Text SEMEVAL 2024
SemEval-2024 Task 7: Numeral-Aware Language Understanding and Generation SEMEVAL 2024
UCSC NLP at SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF) SEMEVAL 2024
CLULab-UofA at SemEval-2024 Task 8: Detecting Machine-Generated Text Using Triplet-Loss-Trained Text Similarity and Text Classification SEMEVAL 2024
SINAI at SemEval-2024 Task 8: Fine-tuning on Words and Perplexity as Features for Detecting Machine Written Text SEMEVAL 2024
LomonosovMSU at SemEval-2024 Task 4: Comparing LLMs and embedder models to identifying propaganda techniques in the content of memes in English for subtasks No1, No2a, and No2b SEMEVAL 2024
AILS-NTUA at SemEval-2024 Task 6: Efficient model tuning for hallucination detection and analysis SEMEVAL 2024
JMI at SemEval 2024 Task 3: Two-step approach for multimodal ECAC using in-context learning with GPT and instruction-tuned Llama models SEMEVAL 2024
MARiA at SemEval 2024 Task-6: Hallucination Detection Through LLMs, MNLI, and Cosine similarity SEMEVAL 2024
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations SEMEVAL 2024
TueCICL at SemEval-2024 Task 8: Resource-efficient approaches for machine-generated text detection SEMEVAL 2024
GeminiPro at SemEval-2024 Task 9: BrainTeaser on Gemini SEMEVAL 2024
Archimedes-AUEB at SemEval-2024 Task 5: LLM explains Civil Procedure SEMEVAL 2024
Weighted Layer Averaging RoBERTa for Black-Box Machine-Generated Text Detection SEMEVAL 2024