Papers Answer Generation
“Answer Generation” 태그가 달린 논문 484편 · 필터 해제
GANDR: Claim Auditing for Verifiable Legal Answer Generation
In high-stakes domains such as legal practice, a language-model answer is only useful to the extent that a reader can verify each claim against the source the system cites. Current grounded-generation pipelines score the…
Answer GenerationBIT.UA at BioASQ 14B: Modular Retrieval with pg_textsearch and Qdrant, and Agent-Based Answer Generation
This paper describes the participation of the BIT.UA team from the University of Aveiro in the 14th edition of the BioASQ Task B challenge on biomedical question answering. Building on our previous submissions, we introd…
Question AnsweringAnswer GenerationA Tree-based RAG Framework for Evidence-Intensive QA via Adaptive Planning and Topology-Aware Evidence Gathering
Recent structured RAG methods leverage tree- or graph-based reasoning structures to improve multi-hop QA. However, they face key limitations in evidence-intensive QA, where answering a question requires synthesizing info…
Answer GenerationFrom Documents to Reasoning: A Validated Synthetic Data Pipeline and Semantic-Aware Fine-Tuning for Financial Numerical Reasoning
Financial question answering (QA) has emerged as a key benchmark for evaluating the performance of Large Language Models (LLMs) on domain-specific tasks involving complex data formats such as tables, charts, and rich tex…
Synthetic Data GenerationSemantic SimilarityQuestion AnsweringAnswer GenerationLivingRAG: Augmenting Graph RAG with Experience
Graph-based RAG improves multi-hop question answering by organizing evidence as a knowledge graph. However, most existing RAG systems process each query in isolation and discard useful reasoning from the LLM's response a…
Multi-hop Question AnsweringAnswer GenerationTAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding
Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To address this challenge, we propose TAU-Agent, an agentic retrieval-augmen…
Answer GenerationVideo CaptioningQuery-Side Attacks on GNN-Based KGQA: Tracing Failures from Entity Linking to Answer Generation
GNN-based Knowledge Graph Question Answering (KGQA) pipelines process queries through four discrete stages: entity linking, subgraph retrieval, GNN reasoning, and answer generation. Standard robustness evaluations confla…
Graph Question AnsweringAnswer GenerationEntity LinkingCoarse Indexing, Fine Evidence: Decoupling Temporal Granularity in Long-Video RAG
Graph-based retrieval-augmented generation (RAG) provides a scalable paradigm for long-video understanding, but existing systems typically inherit a fixed temporal granularity from video segmentation when constructing th…
Video SegmentationAnswer GenerationWhen Failures Propagate: Causal Failure Attribution in Agentic Retrieval-Augmented Generation
Agentic retrieval-augmented generation (RAG) interleaves retrieval, reasoning, and answer generation across multiple hops. A retrieval error at hop 1 can surface only as a wrong answer at hop 3, while later retrieval can…
Answer GenerationFTA-Mem: Fact-Time-Affect Anchored Memory for Low-Density Long-Term Dialogue
Long-term emotional-support agents require memory mechanisms for personalized understanding across sessions. However, emotional-support dialogue is often low-density: turns are incomplete, evidence is scattered, and user…
Question AnsweringAnswer GenerationGLaQ: Grounding Latent Queries in Visual Evidence for Multimodal Reasoning
Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence, however, remains difficult to preserve and reuse across text-based…
Reinforcement LearningMultimodal ReasoningAnswer GenerationMARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination
We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent orchestration for clinical reasoning. MARC coordinates role-special…
Prompt EngineeringAnswer GenerationHybridRAG-BN: A Retrieval-Augmented Framework with Fine-Tuned Verification for Bangla KBQA
Knowledge-base question answering (KBQA) systems rely on effective retrieval and reasoning mechanisms to generate accurate answers from external knowledge sources. However, developing reliable KBQA systems for low-resour…
Question AnsweringAnswer GenerationHalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification
Large language models can generate fluent Arabic answers while introducing factual errors that are difficult to identify and verify. Existing Arabic hallucination resources often assign a binary label to an entire respon…
Explanation GenerationQuestion SelectionAnswer GenerationTrajWiki: Source-Grounded Memory Trajectories for Long-Horizon Dialogue Agents
Large language model agents have shown strong capabilities in generating coherent and contextually appropriate responses, yet robust long-horizon dialogue remains limited by the lack of external memory that is traceable,…
Answer GenerationFinDeepIndicator: Benchmarking Deep Research Agents in End-to-End Financial Indicator Construction
Financial indicators are essential tools for transforming raw financial data into interpretable measures for various downstream tasks, such as valuation, risk assessment, and economic analysis. However, existing financia…
Answer GenerationRRM: Experience-Driven Reflective Retrieval Memory for Long-Horizon Multimodal Reasoning
Existing multimodal long-term memory agents use external memory to overcome the limited context available for long videos. However, most methods emphasize what to store rather than how stored memory should be retrieved. …
Multimodal ReasoningAnswer GenerationThinking Once Is Enough: Intermediate-Layer Evidence Routing for High-Resolution VQA
High-resolution visual question answering (HR-VQA) is often treated as a problem of insufficient evidence acquisition, where failing multimodal large language models must inspect images again through cropping, re-encodin…
Visual Question AnsweringAnswer GenerationBeyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding
Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus on retaining relevant visual content as explicit evidence. Yet makin…
Answer GenerationViewMind3D: Modular View-Aware Inference for Training-Free 3D-QA
Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a key capability for embodied AI and robotic perception. However, most e…
Question AnsweringSpatial ReasoningAnswer Generation3D Reconstruction