Papers Language Modelling
“Language Modelling” 태그가 달린 논문 17,662편 · 필터 해제
Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
In this paper, we explore the use of a text-only, autoregressive language modeling approach for the extraction of referring expressions from visually grounded dialogue. More specifically, the aim is to investigate the ex…
Language ModelingLanguage ModellingLarge Language Modelparameter-efficient fine-tuning+1mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
Multivariate time series anomaly detection (MTS-AD) is critical in domains like healthcare, cybersecurity, and industrial monitoring, yet remains challenging due to complex inter-variable dependencies, temporal dynamics,…
Anomaly DetectionBenchmarkingLanguage ModelingLanguage Modelling+4Data Efficacy for Language Model Training
Data is fundamental to the training of language models (LM). Recent research has been dedicated to data efficiency, which aims to maximize performance by selecting a minimal or optimal subset of training data. Techniques…
Language ModelingLanguage ModellingmodelCan "consciousness" be observed from large language model (LLM) internal states? Dissecting LLM representations obtained from Theory of Mind test with Integrated Information Theory and Span Representation analysis
Integrated Information Theory (IIT) provides a quantitative framework for explaining consciousness phenomenon, positing that conscious systems comprise elements integrated through causal properties. We apply IIT 3.0 and …
Explainable Artificial Intelligence (XAI)Interpretable Machine LearningLanguage ModelingLanguage Modelling+1AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated Text
In today's digital world, casual user-generated content often contains subtle cues that may inadvertently expose sensitive personal attributes. Such risks underscore the growing importance of effective text anonymization…
Contrastive LearningLanguage ModelingLanguage ModellingLarge Language Model+1Large Language Model Agent for Modular Task Execution in Drug Discovery
We present a modular framework powered by large language models (LLMs) that automates and streamlines key tasks across the early-stage computational drug discovery pipeline. By combining LLM reasoning with domain-specifi…
Drug DiscoveryLanguage ModelingLanguage ModellingLarge Language Model+2Language Modeling by Language Models
Can we leverage LLMs to model the process of discovering novel language model (LM) architectures? Inspired by real research, we propose a multi-agent LLM approach that simulates the conventional stages of research, from …
Code GenerationLanguage ModelingLanguage ModellingEnterprise Large Language Model Evaluation Benchmark
Large Language Models (LLMs) ) have demonstrated promise in boosting productivity across AI-powered tools, yet existing benchmarks like Massive Multitask Language Understanding (MMLU) inadequately assess enterprise-speci…
Language Model EvaluationLanguage ModelingLanguage ModellingLarge Language Model+4Case-based Reasoning Augmented Large Language Model Framework for Decision Making in Realistic Safety-Critical Driving Scenarios
Driving in safety-critical scenarios requires quick, context-aware decision-making grounded in both situational understanding and experiential reasoning. Large Language Models (LLMs), with their powerful general-purpose …
Autonomous DrivingDecision MakingDomain AdaptationIn-Context Learning+5Towards Community-Driven Agents for Machine Learning Engineering
Large language model-based machine learning (ML) agents have shown great promise in automating ML research. However, existing agents typically operate in isolation on a given research problem, without engaging with the b…
Language ModelingLanguage ModellingLarge Language ModelSEED: A Structural Encoder for Embedding-Driven Decoding in Time Series Prediction with LLMs
Multivariate time series forecasting requires models to simultaneously capture variable-wise structural dependencies and generalize across diverse tasks. While structural encoders are effective in modeling feature intera…
Language ModelingLanguage ModellingMultivariate Time Series ForecastingRepresentation Learning+3Automatic Demonstration Selection for LLM-based Tabular Data Classification
A fundamental question in applying In-Context Learning (ICL) for tabular data classification is how to determine the ideal number of demonstrations in the prompt. This work addresses this challenge by presenting an algor…
In-Context LearningLanguage ModelingLanguage ModellingLarge Language ModelOctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling
Different base language model families, such as Llama and Qwen, exhibit divergent behaviors during post-training with reinforcement learning (RL), especially on reasoning-intensive tasks. What makes a base language model…
Language ModelingLanguage ModellingMathreinforcement-learning+2Large Language Model-Driven Code Compliance Checking in Building Information Modeling
This research addresses the time-consuming and error-prone nature of manual code compliance checking in Building Information Modeling (BIM) by introducing a Large Language Model (LLM)-driven approach to semi-automate thi…
Language ModelingLanguage ModellingLarge Language ModelA Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection
Background: The positive predictive value (PPV) of large language model (LLM)-based proofreading for radiology reports is limited due to the low error prevalence. Purpose: To assess whether a three-pass LLM framework enh…
Language ModelingLanguage ModellingLarge Language ModelAALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Large reasoning models (LRMs) achieve impressive reasoning capabilities by generating lengthy chain-of-thoughts, but this "overthinking" incurs high latency and cost without commensurate accuracy gains. In this work, we …
Language ModelingLanguage ModellingLarge Language ModelMathNarrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
With rapidly evolving media narratives, it has become increasingly critical to not just extract narratives from a given corpus but rather investigate, how they develop over time. While popular narrative extraction method…
ArticlesChange Point DetectionLanguage ModelingLanguage Modelling+2Biomed-Enriched: A Biomedical Dataset Enriched with LLMs for Pretraining and Extracting Rare and Hidden Content
We introduce Biomed-Enriched, a biomedical text dataset constructed from PubMed via a two-stage annotation process. In the first stage, a large language model annotates 400K paragraphs from PubMed scientific articles, as…
ArticlesContinual PretrainingLanguage ModelingLanguage Modelling+4GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching
Large language models (LLMs) have shown remarkable capabilities in language understanding and generation. However, such impressive capability typically comes with a substantial model size, which presents significant chal…
Language ModelingLanguage ModellingLarge Language ModelAdapThink: Adaptive Thinking Preferences for Reasoning Language Model
Reinforcement Learning (RL)-based post-training has significantly advanced the complex reasoning capabilities of language models, fostering sophisticated self-reflection processes. However, this ``slow thinking'' paradig…
DiversityLanguage ModelingLanguage ModellingMathematical Reasoning+1