Papers Language Modelling
“Language Modelling” 태그가 달린 논문 17,662편 · 필터 해제
Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility
Language models (LMs) are used for a diverse range of tasks, from question answering to writing fantastical stories. In order to reliably accomplish these tasks, LMs must be able to discern the modal category of a senten…
Language ModelingLanguage ModellingQuestion AnsweringKptLLM++: Towards Generic Keypoint Comprehension with Large Language Model
The emergence of Multimodal Large Language Models (MLLMs) has revolutionized image understanding by bridging textual and visual modalities. However, these models often struggle with capturing fine-grained semantic inform…
Keypoint DetectionLanguage ModelingLanguage ModellingLarge Language Model+1Tactical Decision for Multi-UGV Confrontation with a Vision-Language Model-Based Commander
In multiple unmanned ground vehicle confrontations, autonomously evolving multi-agent tactical decisions from situational awareness remain a significant challenge. Traditional handcraft rule-based methods become vulnerab…
Language ModelingLanguage ModellingLarge Language Modelreinforcement-learning+2Mixture of Experts in Large Language Models
This paper presents a comprehensive review of the Mixture-of-Experts (MoE) architecture in large language models, highlighting its ability to significantly enhance model performance while maintaining minimal computationa…
DiversityLanguage ModelingLanguage ModellingLarge Language Model+2LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification
Verifying the credibility of Cyber Threat Intelligence (CTI) is essential for reliable cybersecurity defense. However, traditional approaches typically treat this task as a static classification problem, relying on handc…
Language ModelingLanguage ModellingLarge Language ModelNatural Language Inference+1LiLM-RDB-SFC: Lightweight Language Model with Relational Database-Guided DRL for Optimized SFC Provisioning
Effective management of Service Function Chains (SFCs) and optimal Virtual Network Function (VNF) placement are critical challenges in modern Software-Defined Networking (SDN) and Network Function Virtualization (NFV) en…
Deep Reinforcement LearningLanguage ModelingLanguage ModellingLarge Language ModelKisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?
Chain-of-thought traces have been shown to improve performance of large language models in a plethora of reasoning tasks, yet there is no consensus on the mechanism through which this performance boost is achieved. To sh…
GSM8KLanguage ModelingLanguage ModellingMathematical ReasoningMLAR: Multi-layer Large Language Model-based Robotic Process Automation Applicant Tracking
This paper introduces an innovative Applicant Tracking System (ATS) enhanced by a novel Robotic process automation (RPA) framework or as further referred to as MLAR. Traditional recruitment processes often encounter bott…
BenchmarkingLanguage ModelingLanguage ModellingLarge Language ModelIceberg: Enhancing HLS Modeling with Synthetic Data
Deep learning-based prediction models for High-Level Synthesis (HLS) of hardware designs often struggle to generalize. In this paper, we study how to close the generalizability gap of these models through pretraining on …
Data AugmentationHigh-Level SynthesisLanguage ModelingLanguage Modelling+2Kodezi Chronos: A Debugging-First Language Model for Repository-Scale, Memory-Driven Code Understanding
Large Language Models (LLMs) have advanced code generation and software automation, but are fundamentally constrained by limited inference-time context and lack of explicit code structure reasoning. We introduce Kodezi C…
Code GenerationLanguage ModelingLanguage ModellingRetrievalByDeWay: Boost Your multimodal LLM with DEpth prompting in a Training-Free Way
We introduce ByDeWay, a training-free framework designed to enhance the performance of Multimodal Large Language Models (MLLMs). ByDeWay uses a novel prompting strategy called Layered-Depth-Based Prompting (LDP), which i…
Depth EstimationHallucinationLanguage ModelingLanguage Modelling+2Lizard: An Efficient Linearization Framework for Large Language Models
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into flexible, subquadratic architectures for infinite-context generation. Transformer-based LLMs fac…
Language ModelingLanguage ModellingMMLURepairing Language Model Pipelines by Meta Self-Refining Competing Constraints at Runtime
Language Model (LM) pipelines can dynamically refine their outputs against programmatic constraints. However, their effectiveness collapses when faced with competing soft constraints, leading to inefficient backtracking …
Language ModelingLanguage ModellingMIDI-VALLE: Improving Expressive Piano Performance Synthesis Through Neural Codec Language Modelling
Generating expressive audio performances from music scores requires models to capture both instrument acoustics and human interpretation. Traditional music performance synthesis pipelines follow a two-stage approach, fir…
Audio SynthesisLanguage Modellingtext-to-speechText to SpeechAudio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models
We present Audio Flamingo 3 (AF3), a fully open state-of-the-art (SOTA) large audio-language model that advances reasoning and understanding across speech, sound, and music. AF3 introduces: (i) AF-Whisper, a unified audi…
Language ModelingLanguage ModellingRepresentation LearningOpen Source Planning & Control System with Language Agents for Autonomous Scientific Discovery
We present a multi-agent system for automation of scientific research tasks, cmbagent. The system is formed by about 30 Large Language Model (LLM) agents and implements a Planning & Control strategy to orchestrate the ag…
Language ModelingLanguage ModellingLarge Language Modelscientific discoverySqueeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model
Reinforcement Learning (RL) has demonstrated its potential to improve the reasoning ability of Large Language Models (LLMs). One major limitation of most existing Reinforcement Finetuning (RFT) methods is that they are o…
Language ModelingLanguage ModellingLarge Language ModelMath+1PrefixAgent: An LLM-Powered Design Framework for Efficient Prefix Adder Optimization
Prefix adders are fundamental arithmetic circuits, but their design space grows exponentially with bit-width, posing significant optimization challenges. Previous works face limitations in performance, generalization, an…
Language ModelingLanguage ModellingLarge Language ModelDifferential Mamba
Sequence models like Transformers and RNNs often overallocate attention to irrelevant context, leading to noisy intermediate representations. This degrades LLM capabilities by promoting hallucinations, weakening long-ran…
Language ModelingLanguage ModellingMambaRetrievalEvolution without Large Models: Training Language Model with Task Principles
A common training approach for language models involves using a large-scale language model to expand a human-provided dataset, which is subsequently used for model training.This method significantly reduces training cost…
Data AugmentationLanguage ModelingLanguage Modelling