Papers Large Language Model
“Large Language Model” 태그가 달린 논문 6,097편 · 필터 해제
DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning
Retrosynthesis, the identification of precursor molecules for a target compound, is pivotal for synthesizing complex molecules, but faces challenges in discovering novel pathways beyond predefined templates. Recent large…
HallucinationLarge Language ModelRetrosynthesisInaugural MOASEI Competition at AAMAS'2025: A Technical Report
We present the Methods for Open Agent Systems Evaluation Initiative (MOASEI) Competition, a multi-agent AI benchmarking event designed to evaluate decision-making under open-world conditions. Built on the free-range-zoo …
BenchmarkingDecision MakingLanguage ModelingLanguage Modelling+1AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models
Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. They adapt to various styles and genres, …
ArticlesLarge Language ModelText DetectionEvaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while another critical component-memory, encompassing how agents memorize, update, an…
Large Language ModelRAGRetrievalRetrieval-augmented GenerationPRIME: Large Language Model Personalization with Cognitive Memory and Thought Processes
Large language model (LLM) personalization aims to align model outputs with individuals' unique preferences and opinions. While recent efforts have implemented various personalization methods, a unified theoretical frame…
Language ModelingLanguage ModellingLarge Language ModelCoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-step
Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal spatial control, as their generation pr…
DenoisingLarge Language ModelMultimodal Large Language ModelBiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization
Large Language Model-enhanced Recommender Systems (LLM-enhanced RSs) have emerged as a powerful approach to improving recommendation quality by leveraging LLMs to generate item representations. Despite these advancements…
FairnessLarge Language ModelRecommendation SystemsBehaviour Space Analysis of LLM-driven Meta-heuristic Discovery
We investigate the behaviour space of meta-heuristic optimisation algorithms automatically generated by Large Language Model driven algorithm discovery methods. Using the Large Language Evolutionary Algorithm (LLaMEA) fr…
Large Language ModelGRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation
Document level Machine Translation (DocMT) approaches often struggle with effectively capturing discourse level phenomena. Existing approaches rely on heuristic rules to segment documents into discourse units, which rare…
Document Level Machine TranslationDocument TranslationLarge Language ModelMachine Translation+1Early Signs of Steganographic Capabilities in Frontier LLMs
Monitoring Large Language Model (LLM) outputs is crucial for mitigating risks from misuse and misalignment. However, LLMs could evade monitoring through steganography: Encoding hidden information within seemingly benign …
Large Language ModelPrompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization
Domain Generalization (DG) seeks to develop a versatile model capable of performing effectively on unseen target domains. Notably, recent advances in pre-trained Visual Foundation Models (VFMs), such as CLIP, have demons…
DescriptiveDisentanglementDomain GeneralizationLarge Language Model+1OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering
Open-domain table question answering traditionally relies on a two-stage pipeline: static table retrieval followed by a closed-domain answer. In contrast, we propose an end-to-end agentic framework that embeds multi-turn…
Language ModelingLanguage ModellingLarge Language ModelQuestion Answering+1LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs
The architecture of multimodal large language models (MLLMs) commonly connects a vision encoder, often based on CLIP-ViT, to a large language model. While CLIP-ViT works well for capturing global image features, it strug…
Large Language ModelThought-Augmented Planning for LLM-Powered Interactive Recommender Agent
Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendations. Large language model-powered (LLM-…
Interactive RecommendationLarge Language ModelRecommendation SystemsUser SimulationAuto-TA: Towards Scalable Automated Thematic Analysis (TA) via Multi-Agent Large Language Models with Reinforcement Learning
Congenital heart disease (CHD) presents complex, lifelong challenges often underrepresented in traditional clinical metrics. While unstructured narratives offer rich insights into patient and caregiver experiences, manua…
Language ModelingLanguage ModellingLarge Language ModelDataset Distillation via Vision-Language Category Prototype
Dataset distillation (DD) condenses large datasets into compact yet informative substitutes, preserving performance comparable to the original dataset while reducing storage, transmission costs, and computational consump…
Dataset DistillationDescriptiveLarge Language ModelWhere, What, Why: Towards Explainable Driver Attention Prediction
Modeling task-driven attention in driving is a fundamental challenge for both autonomous vehicles and cognitive science. Existing methods primarily predict where drivers look by generating spatial heatmaps, but fail to c…
Autonomous DrivingAutonomous VehiclesDriver Attention MonitoringLarge Language Model+2ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence Alignment
We address the task of zero-shot fine-grained video classification, where no video examples or temporal annotations are available for unseen action classes. While contrastive vision-language models such as SigLIP demonst…
Dynamic Time WarpingLarge Language ModelOpen Set Learningtext similarity+2Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval
Text-to-image retrieval (TIR) aims to find relevant images based on a textual query, but existing approaches are primarily based on whole-image captions and lack interpretability. Meanwhile, referring expression segmenta…
Cross-Modal RetrievalImage CaptioningImage RetrievalLarge Language Model+9Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
Existing video segmenter and grounder approaches, exemplified by Sa2VA, directly fuse features within segmentation models. This often results in an undesirable entanglement of dynamic visual information and static semant…
Image SegmentationLarge Language ModelQuestion AnsweringSegmentation+5