Papers Attribute
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MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM
Recent studies have utilized visual large language models (VLMs) to answer not only "Is this face a forgery?" but also "Why is the face a forgery?" These studies introduced forgery-related attributes, such as forgery loc…
AttributeFace SwappingPrompt LearningVisual Question Answering (VQA)Non-Adaptive Adversarial Face Generation
Adversarial attacks on face recognition systems (FRSs) pose serious security and privacy threats, especially when these systems are used for identity verification. In this paper, we propose a novel method for generating …
AttributeFace GenerationFace RecognitionAttributes Shape the Embedding Space of Face Recognition Models
Face Recognition (FR) tasks have made significant progress with the advent of Deep Neural Networks, particularly through margin-based triplet losses that embed facial images into high-dimensional feature spaces. During t…
AttributeFace RecognitionTripletCOLIBRI Fuzzy Model: Color Linguistic-Based Representation and Interpretation
Colors are omnipresent in today's world and play a vital role in how humans perceive and interact with their surroundings. However, it is challenging for computers to imitate human color perception. This paper introduces…
AttributeMarketingRef-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models
Long-context language models (LCLMs) have exhibited impressive capabilities in long-context understanding tasks. Among these, long-context referencing -- a crucial task that requires LCLMs to attribute items of interest …
AttributeBenchmarkingLong-Context UnderstandingModel Parallelism With Subnetwork Data Parallelism
Distributed pre-training of large models at scale often imposes heavy memory demands on individual nodes and incurs significant intra-node communication costs. We propose a novel alternative approach that reduces the mem…
AttributeFederated LearningmodelBradley-Terry and Multi-Objective Reward Modeling Are Complementary
Reward models trained on human preference data have demonstrated strong effectiveness in aligning Large Language Models (LLMs) with human intent under the framework of Reinforcement Learning from Human Feedback (RLHF). H…
AttributeregressionEvaluating Attribute Confusion in Fashion Text-to-Image Generation
Despite the rapid advances in Text-to-Image (T2I) generation models, their evaluation remains challenging in domains like fashion, involving complex compositional generation. Recent automated T2I evaluation methods lever…
Attributecross-modal alignmentImage GenerationQuestion Answering+5LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance
While large multi-modal models (LMMs) demonstrate promising capabilities in segmentation and comprehension, they still struggle with two limitations: inaccurate segmentation and hallucinated comprehension. These challeng…
AttributeSegmentationSemantic SegmentationEmergent Semantics Beyond Token Embeddings: Transformer LMs with Frozen Visual Unicode Representations
Understanding the locus of semantic representation in large language models (LLMs) is crucial for interpretability and architectural innovation. The dominant paradigm posits that trainable input embeddings serve as found…
AttributeMMLUAn analysis of vision-language models for fabric retrieval
Effective cross-modal retrieval is essential for applications like information retrieval and recommendation systems, particularly in specialized domains such as manufacturing, where product information often consists of …
AttributeCross-Modal RetrievalImage RetrievalInformation Retrieval+3MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection
We present the first work demonstrating that a pure Mamba block can achieve efficient Dense Global Fusion, meanwhile guaranteeing top performance for camera-LiDAR multi-modal 3D object detection. Our motivation stems fro…
3D Object DetectionAttributeLong-range modelingMamba+3Helping CLIP See Both the Forest and the Trees: A Decomposition and Description Approach
Vision-Language Models (VLMs) like CLIP achieve cross-modal semantic alignment through contrastive learning, exhibiting robust zero-shot generalization. Traditional prompt engineering, however, predominantly relies on co…
AttributeContrastive LearningPrompt EngineeringTest-time Adaptation+1IndianBailJudgments-1200: A Multi-Attribute Dataset for Legal NLP on Indian Bail Orders
Legal NLP remains underdeveloped in regions like India due to the scarcity of structured datasets. We introduce IndianBailJudgments-1200, a new benchmark dataset comprising 1200 Indian court judgments on bail decisions, …
AttributeFairnessJurisprudenceLegal ReasoningThe Trilemma of Truth in Large Language Models
We often attribute human characteristics to large language models (LLMs) and claim that they "know" certain things. LLMs have an internal probabilistic knowledge that represents information retained during training. How …
AttributeConformal PredictionKnowledge DistillationMultiple Instance Learning+1FOCUS: Fine-grained Optimization with Semantic Guided Understanding for Pedestrian Attributes Recognition
Pedestrian attribute recognition (PAR) is a fundamental perception task in intelligent transportation and security. To tackle this fine-grained task, most existing methods focus on extracting regional features to enrich …
AttributeContrastive LearningPedestrian Attribute RecognitionSAC: A Framework for Measuring and Inducing Personality Traits in LLMs with Dynamic Intensity Control
Large language models (LLMs) have gained significant traction across a wide range of fields in recent years. There is also a growing expectation for them to display human-like personalities during interactions. To meet t…
AttributeText2Cypher Across Languages: Evaluating Foundational Models Beyond English
Recent advances in large language models have enabled natural language interfaces that translate user questions into database queries, such as Text2SQL, Text2SPARQL, and Text2Cypher. While these interfaces enhance databa…
AttributeText2SparqlStyle-Aligned Image Composition for Robust Detection of Abnormal Cells in Cytopathology
Challenges such as the lack of high-quality annotations, long-tailed data distributions, and inconsistent staining styles pose significant obstacles to training neural networks to detect abnormal cells in cytopathology r…
AttributeCell DetectionIPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
Video Large Language Models (VideoLLMs) have demonstrated remarkable understanding capabilities, but are found struggling to tackle multi-shot scenarios,e.g., video clips with varying camera angles or scene changes. This…
AttributeQuestion AnsweringVideo Understanding