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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 4101–4150 of 17610 papers

TitleStatusHype
A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction—0
Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection—0
GradualDiff-Fed: A Federated Learning Specialized Framework for Large Language Model—0
PARALLELPROMPT: Extracting Parallelism from Large Language Model Queries—0
Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms—0
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems—0
Reflective Verbal Reward Design for Pluralistic Alignment—0
Can Generated Images Serve as a Viable Modality for Text-Centric Multimodal Learning?—0
Computational Approaches to Understanding Large Language Model Impact on Writing and Information Ecosystems—0
Challenges in Grounding Language in the Real World—0
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization—0
LLMs in Coding and their Impact on the Commercial Software Engineering Landscape—0
RAS-Eval: A Comprehensive Benchmark for Security Evaluation of LLM Agents in Real-World EnvironmentsCode0
Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks—0
Finance Language Model Evaluation (FLaME)—0
From RAG to Agentic: Validating Islamic-Medicine Responses with LLM Agents—0
DiffusionBlocks: Blockwise Training for Generative Models via Score-Based Diffusion—0
Lightweight Relevance Grader in RAGCode0
From What to Respond to When to Respond: Timely Response Generation for Open-domain Dialogue AgentsCode0
Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees—0
Don't Make It Up: Preserving Ignorance Awareness in LLM Fine-Tuning—0
ASCD: Attention-Steerable Contrastive Decoding for Reducing Hallucination in MLLM—0
Hypothesis Testing for Quantifying LLM-Human Misalignment in Multiple Choice Settings—0
Interpreting Biomedical VLMs on High-Imbalance Out-of-Distributions: An Insight into BiomedCLIP on RadiologyCode0
Thinking in Directivity: Speech Large Language Model for Multi-Talker Directional Speech Recognition—0
ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations—0
Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization—0
EmoNews: A Spoken Dialogue System for Expressive News ConversationsCode0
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining—0
NTU Speechlab LLM-Based Multilingual ASR System for Interspeech MLC-SLM Challenge 2025—0
CFBenchmark-MM: Chinese Financial Assistant Benchmark for Multimodal Large Language Model—0
Leveraging In-Context Learning for Language Model Agents—0
VIS-Shepherd: Constructing Critic for LLM-based Data Visualization GenerationCode0
Bi-directional Context-Enhanced Speech Large Language Models for Multilingual Conversational ASR—0
Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models—0
Qwen vs. Gemma Integration with Whisper: A Comparative Study in Multilingual SpeechLLM Systems—0
PRISM2: Unlocking Multi-Modal General Pathology AI with Clinical Dialogue—0
Value-Free Policy Optimization via Reward PartitioningCode0
HypER: Literature-grounded Hypothesis Generation and Distillation with Provenance—0
SciSage: A Multi-Agent Framework for High-Quality Scientific Survey Generation—0
Information fusion strategy integrating pre-trained language model and contrastive learning for materials knowledge mining—0
From Human to Machine Psychology: A Conceptual Framework for Understanding Well-Being in Large Language Model—0
Is your batch size the problem? Revisiting the Adam-SGD gap in language modeling—0
Information Suppression in Large Language Models: Auditing, Quantifying, and Characterizing Censorship in DeepSeek—0
Semantic Preprocessing for LLM-based Malware Analysis—0
Large Language Model-Powered Conversational Agent Delivering Problem-Solving Therapy (PST) for Family Caregivers: Enhancing Empathy and Therapeutic Alliance Using In-Context Learning—0
FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations—0
Improving Large Language Model Safety with Contrastive Representation LearningCode0
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution—0
Investigating the Potential of Large Language Model-Based Router Multi-Agent Architectures for Foundation Design Automation: A Task Classification and Expert Selection Study—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