SOTAVerified

Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

Showing 20012050 of 17610 papers

TitleStatusHype
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question AnsweringCode1
STaR-GATE: Teaching Language Models to Ask Clarifying QuestionsCode1
Common Sense Enhanced Knowledge-based Recommendation with Large Language ModelCode1
Sequential Recommendation with Latent Relations based on Large Language ModelCode1
Homogeneous Tokenizer Matters: Homogeneous Visual Tokenizer for Remote Sensing Image UnderstandingCode1
Content-Based Collaborative Generation for Recommender SystemsCode1
Optimization-based Prompt Injection Attack to LLM-as-a-JudgeCode1
JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue DatasetCode1
Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model EvaluatorsCode1
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept DescriptionsCode1
Generation of Asset Administration Shell with Large Language Model Agents: Toward Semantic Interoperability in Digital Twins in the Context of Industry 4.0Code1
A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based PerspectiveCode1
MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge DistillationCode1
WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language ModelsCode1
Lexicon-Level Contrastive Visual-Grounding Improves Language ModelingCode1
Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language ModelCode1
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment RecommendationCode1
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language TranslationCode1
CLIP-VIS: Adapting CLIP for Open-Vocabulary Video Instance SegmentationCode1
Prioritized Semantic Learning for Zero-shot Instance NavigationCode1
Subjective-Aligned Dataset and Metric for Text-to-Video Quality AssessmentCode1
Meta-Prompting for Automating Zero-shot Visual Recognition with LLMsCode1
Training A Small Emotional Vision Language Model for Visual Art ComprehensionCode1
SQ-LLaVA: Self-Questioning for Large Vision-Language AssistantCode1
Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk PredictionCode1
CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language ModelCode1
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language ModelsCode1
Emergence of Social Norms in Generative Agent Societies: Principles and ArchitectureCode1
LookupFFN: Making Transformers Compute-lite for CPU inferenceCode1
Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal ModelsCode1
MoralBERT: A Fine-Tuned Language Model for Capturing Moral Values in Social DiscussionsCode1
Elephants Never Forget: Testing Language Models for Memorization of Tabular DataCode1
FontCLIP: A Semantic Typography Visual-Language Model for Multilingual Font ApplicationsCode1
ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language ModelCode1
TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned DecisionCode1
Personalized LoRA for Human-Centered Text UnderstandingCode1
ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical NotesCode1
Algorithmic progress in language modelsCode1
Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-ThoughtCode1
Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis AgentsCode1
IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code GeneratorsCode1
Generative News RecommendationCode1
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional EncodingCode1
Multi-modal Instruction Tuned LLMs with Fine-grained Visual PerceptionCode1
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing DetectionCode1
A Cross-Modal Approach to Silent Speech with LLM-Enhanced RecognitionCode1
NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free AttentionCode1
DMoERM: Recipes of Mixture-of-Experts for Effective Reward ModelingCode1
Merging Text Transformer Models from Different InitializationsCode1
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-CommerceCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified