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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 5001–5050 of 17610 papers

TitleStatusHype
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMsCode0
CoLM-DSR: Leveraging Neural Codec Language Modeling for Multi-Modal Dysarthric Speech Reconstruction—0
Flash-VStream: Memory-Based Real-Time Understanding for Long Video StreamsCode3
Figuratively Speaking: Authorship Attribution via Multi-Task Figurative Language ModelingCode0
Memory Is All You Need: An Overview of Compute-in-Memory Architectures for Accelerating Large Language Model Inference—0
Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences—0
Discovering Preference Optimization Algorithms with and for Large Language ModelsCode2
An Empirical Study of Mamba-based Language Models—0
Guiding In-Context Learning of LLMs through Quality Estimation for Machine TranslationCode0
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag CompetitionCode0
OLMES: A Standard for Language Model Evaluations—0
Let's Go Real Talk: Spoken Dialogue Model for Face-to-Face Conversation—0
Analyzing constrained LLM through PDFA-learningCode0
Collective Constitutional AI: Aligning a Language Model with Public InputCode1
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Large Language Model Unlearning via Embedding-Corrupted PromptsCode1
A Study of Backdoors in Instruction Fine-tuned Language Models—0
Multimodal Table UnderstandingCode3
Supportiveness-based Knowledge Rewriting for Retrieval-augmented Language Modeling—0
MobileAgentBench: An Efficient and User-Friendly Benchmark for Mobile LLM Agents—0
Enhancing Differential Testing With LLMs For Testing Deep Learning Libraries—0
Real2Code: Reconstruct Articulated Objects via Code Generation—0
Markov Constraint as Large Language Model Surrogate—0
Flextron: Many-in-One Flexible Large Language Model—0
Large Language Model-empowered multimodal strain sensory system for shape recognition, monitoring, and human interaction of tensegrity—0
Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis—0
Test-Time Fairness and Robustness in Large Language Models—0
MambaLRP: Explaining Selective State Space Sequence ModelsCode1
LLAMAFUZZ: Large Language Model Enhanced Greybox Fuzzing—0
Scaling Large Language Model-based Multi-Agent CollaborationCode1
TernaryLLM: Ternarized Large Language Model—0
Scholarly Question Answering using Large Language Models in the NFDI4DataScience GatewayCode0
World Models with Hints of Large Language Models for Goal Achieving—0
Teaching Language Models to Self-Improve by Learning from Language Feedback—0
VersiCode: Towards Version-controllable Code GenerationCode1
PLUM: Improving Code LMs with Execution-Guided On-Policy Preference Learning Driven By Synthetic Test Cases—0
Paying More Attention to Source Context: Mitigating Unfaithful Translations from Large Language ModelCode0
BvSP: Broad-view Soft Prompting for Few-Shot Aspect Sentiment Quad PredictionCode0
HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination EvaluationCode0
Evolving Subnetwork Training for Large Language ModelsCode0
UVIS: Unsupervised Video Instance Segmentation—0
Simple and Effective Masked Diffusion Language ModelsCode4
Multi-objective Reinforcement learning from AI FeedbackCode0
Beyond Bare Queries: Open-Vocabulary Object Grounding with 3D Scene Graph—0
Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingCode4
RS-Agent: Automating Remote Sensing Tasks through Intelligent AgentCode2
Towards Signal Processing In Large Language Models—0
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific LiteratureCode1
TRINS: Towards Multimodal Language Models that Can ReadCode0
NarrativeBridge: Enhancing Video Captioning with Causal-Temporal Narrative—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified