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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1100 of 17610 papers

TitleStatusHype
Real-Time Evaluation Models for RAG: Who Detects Hallucinations Best?—0
MoQa: Rethinking MoE Quantization with Multi-stage Data-model Distribution Awareness—0
MemInsight: Autonomous Memory Augmentation for LLM Agents—0
Shared Global and Local Geometry of Language Model Embeddings—0
Socially Constructed Treatment Plans: Analyzing Online Peer Interactions to Understand How Patients Navigate Complex Medical Conditions—0
Large Language Model Agent: A Survey on Methodology, Applications and ChallengesCode7
Enhancing Domain-Specific Encoder Models with LLM-Generated Data: How to Leverage Ontologies, and How to Do Without Them—0
VALLR: Visual ASR Language Model for Lip Reading—0
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models—0
VoxRep: Enhancing 3D Spatial Understanding in 2D Vision-Language Models via Voxel Representation—0
Outlier dimensions favor frequent tokens in language models—0
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video UnderstandingCode1
Controlling Large Language Model with Latent ActionsCode0
FakeReasoning: Towards Generalizable Forgery Detection and Reasoning—0
Mobile-VideoGPT: Fast and Accurate Video Understanding Language ModelCode2
LLM-Gomoku: A Large Language Model-Based System for Strategic Gomoku with Self-Play and Reinforcement Learning—0
Prompt, Divide, and Conquer: Bypassing Large Language Model Safety Filters via Segmented and Distributed Prompt Processing—0
Using large language models to produce literature reviews: Usages and systematic biases of microphysics parametrizations in 2699 publications—0
Prompting Vision-Language Model for Nuclei Instance Segmentation and ClassificationCode0
MoRE-LLM: Mixture of Rule Experts Guided by a Large Language ModelCode0
InfoBid: A Simulation Framework for Studying Information Disclosure in Auctions with Large Language Model-based Agents—0
D4R -- Exploring and Querying Relational Graphs Using Natural Language and Large Language Models -- the Case of Historical Documents—0
Dynamic Pyramid Network for Efficient Multimodal Large Language ModelCode0
Can Large Language Models Predict Associations Among Human Attitudes?—0
Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face DetectorCode2
ASGO: Adaptive Structured Gradient Optimization—0
A Multilingual, Culture-First Approach to Addressing Misgendering in LLM ApplicationsCode0
CFunModel: A "Funny" Language Model Capable of Chinese Humor Generation and Processing—0
AutoRad-Lung: A Radiomic-Guided Prompting Autoregressive Vision-Language Model for Lung Nodule Malignancy Prediction—0
LogicQA: Logical Anomaly Detection with Vision Language Model Generated Questions—0
The cell as a token: high-dimensional geometry in language models and cell embeddings—0
Exploring the Effect of Robotic Embodiment and Empathetic Tone of LLMs on Empathy Elicitation—0
RALLRec+: Retrieval Augmented Large Language Model Recommendation with ReasoningCode0
Rosetta-PL: Propositional Logic as a Benchmark for Large Language Model Reasoning—0
PHEONA: An Evaluation Framework for Large Language Model-based Approaches to Computational Phenotyping—0
OAEI-LLM-T: A TBox Benchmark Dataset for Understanding Large Language Model Hallucinations in Ontology Matching—0
Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery—0
A-MESS: Anchor based Multimodal Embedding with Semantic Synchronization for Multimodal Intent Recognition—0
Improved Alignment of Modalities in Large Vision Language Models—0
CAFe: Unifying Representation and Generation with Contrastive-Autoregressive FinetuningCode1
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning—0
FireEdit: Fine-grained Instruction-based Image Editing via Region-aware Vision Language Model—0
SemEval-2025 Task 9: The Food Hazard Detection Challenge—0
1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training—0
LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy PreservationCode1
CubeRobot: Grounding Language in Rubik's Cube Manipulation via Vision-Language Model—0
Exploring Textual Semantics Diversity for Image Transmission in Semantic Communication Systems using Visual Language Model—0
Generative Linguistics, Large Language Models, and the Social Nature of Scientific Success—0
Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image AnalysisCode2
CoLLM: A Large Language Model for Composed Image RetrievalCode1
Show:102550
← PrevPage 22 of 353Next →
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