Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
Overview of the TalentCLEF 2025: Skill and Job Title Intelligence for Human Capital Management
Advances in natural language processing and large language models are driving a major transformation in Human Capital Management, with a growing interest in building smart systems based on language technologies for talen…
Contrastive LearningData AugmentationInformation RetrievalManagement+1MCoT-RE: Multi-Faceted Chain-of-Thought and Re-Ranking for Training-Free Zero-Shot Composed Image Retrieval
Composed Image Retrieval (CIR) is the task of retrieving a target image from a gallery using a composed query consisting of a reference image and a modification text. Among various CIR approaches, training-free zero-shot…
Image RetrievalRe-RankingRetrievalCATVis: Context-Aware Thought Visualization
EEG-based brain-computer interfaces (BCIs) have shown promise in various applications, such as motor imagery and cognitive state monitoring. However, decoding visual representations from EEG signals remains a significant…
cross-modal alignmentEEGImage GenerationMotor Imagery+1SAMURAI: Shape-Aware Multimodal Retrieval for 3D Object Identification
Retrieving 3D objects in complex indoor environments using only a masked 2D image and a natural language description presents significant challenges. The ROOMELSA challenge limits access to full 3D scene context, complic…
3D Object RetrievalObjectRe-RankingRetrievalRAG-VisualRec: An Open Resource for Vision- and Text-Enhanced Retrieval-Augmented Generation in Recommendation
This paper addresses the challenge of developing multimodal recommender systems for the movie domain, where limited metadata (e.g., title, genre) often hinders the generation of robust recommendations. We introduce a res…
Collaborative FilteringData AugmentationMulti-modal RecommendationRAG+3IRanker: Towards Ranking Foundation Model
Ranking tasks are ubiquitous, encompassing applications such as recommendation systems, LLM routing, and item re-ranking. We propose to unify these tasks using a single ranking foundation model (FM), as it eliminates the…
GSM8KmodelPassage RankingRecommendation Systems+3RMIT-ADM+S at the SIGIR 2025 LiveRAG Challenge
This paper presents the RMIT--ADM+S participation in the SIGIR 2025 LiveRAG Challenge. Our Generation-Retrieval-Augmented Generation (GRAG) approach relies on generating a hypothetical answer that is used in the retrieva…
Answer GenerationLanguage ModelingLanguage ModellingLarge Language Model+3SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
Document Visual Question Answering (DocVQA) is a practical yet challenging task, which is to ask questions based on documents while referring to multiple pages and different modalities of information, e.g, images and tab…
document understandingQuestion AnsweringRAGRe-Ranking+3CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Models
Recommender systems (RSs) are designed to retrieve candidate items a user might be interested in from a large pool. A common approach is using graph neural networks (GNNs) to capture high-order interaction relationships.…
Collaborative FilteringRecommendation SystemsRe-RankingRetrievalQuery-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking
Recent work has identified retrieval heads (Wu et al., 2025b), a subset of attention heads responsible for retrieving salient information in long-context language models (LMs), as measured by their copy-paste behavior in…
Re-RankingRetrievalLearning to Reason Across Parallel Samples for LLM Reasoning
Scaling test-time compute brings substantial performance gains for large language models (LLMs). By sampling multiple answers and heuristically aggregate their answers (e.g., either through majority voting or using verif…
MathRe-RankingADAM: Autonomous Discovery and Annotation Model using LLMs for Context-Aware Annotations
Object detection models typically rely on predefined categories, limiting their ability to identify novel objects in open-world scenarios. To overcome this constraint, we introduce ADAM: Autonomous Discovery and Annotati…
Objectobject-detectionObject DetectionRe-RankingLocality Preserving Markovian Transition for Instance Retrieval
Diffusion-based re-ranking methods are effective in modeling the data manifolds through similarity propagation in affinity graphs. However, positive signals tend to diminish over several steps away from the source, reduc…
Re-RankingRetrievalNR4DER: Neural Re-ranking for Diversified Exercise Recommendation
With the widespread adoption of online education platforms, an increasing number of students are gaining new knowledge through Massive Open Online Courses (MOOCs). Exercise recommendation have made strides toward improvi…
Re-RankingLearning Distributions over Permutations and Rankings with Factorized Representations
Learning distributions over permutations is a fundamental problem in machine learning, with applications in ranking, combinatorial optimization, structured prediction, and data association. Existing methods rely on mixtu…
Combinatorial OptimizationRe-RankingStructured PredictionVariational InferenceSA-Person: Text-Based Person Retrieval with Scene-aware Re-ranking
Text-based person retrieval aims to identify a target individual from a gallery of images based on a natural language description. It presents a significant challenge due to the complexity of real-world scenes and the am…
Cross-Modal RetrievalPerson RetrievalRe-RankingRetrieval+2Deep Retrieval at CheckThat! 2025: Identifying Scientific Papers from Implicit Social Media Mentions via Hybrid Retrieval and Re-Ranking
We present the methodology and results of the Deep Retrieval team for subtask 4b of the CLEF CheckThat! 2025 competition, which focuses on retrieving relevant scientific literature for given social media posts. To addres…
Large Language ModelRe-RankingRetrievalSemantic RetrievalmRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation
Large Vision-Language Models (LVLMs) have made remarkable strides in multimodal tasks such as visual question answering, visual grounding, and complex reasoning. However, they remain limited by static training data, susc…
Question AnsweringRAGRe-RankingRetrieval+3Distilling Closed-Source LLM's Knowledge for Locally Stable and Economic Biomedical Entity Linking
Biomedical entity linking aims to map nonstandard entities to standard entities in a knowledge base. Traditional supervised methods perform well but require extensive annotated data to transfer, limiting their usage in l…
Entity LinkingRe-RankingREARANK: Reasoning Re-ranking Agent via Reinforcement Learning
We present REARANK, a large language model (LLM)-based listwise reasoning reranking agent. REARANK explicitly reasons before reranking, significantly improving both performance and interpretability. Leveraging reinforcem…
Data AugmentationInformation RetrievalLanguage ModelingLanguage Modelling+6