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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 5551–5600 of 17610 papers

TitleStatusHype
A statistically consistent measure of Semantic Variability using Language Models—0
INSIGHT: Enhancing Autonomous Driving Safety through Vision-Language Models on Context-Aware Hazard Detection and Edge Case Evaluation—0
BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning—0
Brain-inspired sparse training enables Transformers and LLMs to perform as fully connected—0
Estimating the Probability of Sampling a Trained Neural Network at Random—0
Improving LLM Unlearning Robustness via Random PerturbationsCode0
Intrinsic Tensor Field Propagation in Large Language Models: A Novel Approach to Contextual Information Flow—0
Importing Phantoms: Measuring LLM Package Hallucination Vulnerabilities—0
An Efficient Approach for Machine Translation on Low-resource Languages: A Case Study in Vietnamese-Chinese—0
Can AI Solve the Peer Review Crisis? A Large Scale Cross Model Experiment of LLMs' Performance and Biases in Evaluating over 1000 Economics Papers—0
Offline Learning for Combinatorial Multi-armed Bandits—0
SELMA: A Speech-Enabled Language Model for Virtual Assistant Interactions—0
Towards the Worst-case Robustness of Large Language Models—0
Mobile Robot Navigation Using Hand-Drawn Maps: A Vision Language Model Approach—0
Resolving Editing-Unlearning Conflicts: A Knowledge Codebook Framework for Large Language Model Updating—0
Structural Embedding Projection for Contextual Large Language Model Inference—0
Scaling Laws for Differentially Private Language Models—0
Loss Functions and Operators Generated by f-Divergences—0
Vision-Language Model Selection and Reuse for Downstream Adaptation—0
Token-Hungry, Yet Precise: DeepSeek R1 Highlights the Need for Multi-Step Reasoning Over Speed in MATH—0
CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering—0
Differentially Private Steering for Large Language Model AlignmentCode0
Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks—0
Investigating Tax Evasion Emergence Using Dual Large Language Model and Deep Reinforcement Learning Powered Agent-based Simulation—0
Economic Rationality under Specialization: Evidence of Decision Bias in AI Agents—0
Efficiency and Effectiveness of LLM-Based Summarization of Evidence in Crowdsourced Fact-Checking—0
CLEAR: Cue Learning using Evolution for Accurate Recognition Applied to Sustainability Data Extraction—0
Fine-tuning LLaMA 2 interference: a comparative study of language implementations for optimal efficiency—0
Enhancing Large Language Model Efficiencyvia Symbolic Compression: A Formal Approach Towards Interpretability—0
Can Generative LLMs Create Query Variants for Test Collections? An Exploratory StudyCode0
DReSS: Data-driven Regularized Structured Streamlining for Large Language Models—0
DINT Transformer—0
Is Conversational XAI All You Need? Human-AI Decision Making With a Conversational XAI AssistantCode0
BreezyVoice: Adapting TTS for Taiwanese Mandarin with Enhanced Polyphone Disambiguation -- Challenges and Insights—0
From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors—0
Query-Aware Learnable Graph Pooling Tokens as Prompt for Large Language Models—0
Leveraging Multimodal LLM for Inspirational User Interface SearchCode0
Large Language Models for Single-Step and Multi-Step Flight Trajectory Prediction—0
Prompt-oriented Output of Culture-Specific Items in Translated African Poetry by Large Language Model: An Initial Multi-layered Tabular Review—0
Learning Free Token Reduction for Multi-Modal Large Language Models—0
Planning with Vision-Language Models and a Use Case in Robot-Assisted Teaching—0
Optimizing Large Language Model Training Using FP4 Quantization—0
Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling—0
Large Language Model Critics for Execution-Free Evaluation of Code ChangesCode0
"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalism—0
Language Modelling for Speaker Diarization in Telephonic Interviews—0
Multiple Abstraction Level Retrieve Augment Generation—0
An LLM Benchmark for Addressee Recognition in Multi-modal Multi-party Dialogue—0
Implementation of a Generative AI Assistant in K-12 Education: The CyberScholar Initiative—0
Document Screenshot Retrievers are Vulnerable to Pixel Poisoning AttacksCode0
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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