SOTAVerified

Conversational Question Answering

Papers

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Showing 26–50 of 142 papers

TitleStatusHype
Conversational Question Answering with Reformulations over Knowledge Graph—0
S2M: Converting Single-Turn to Multi-Turn Datasets for Conversational Question Answering—0
PCoQA: Persian Conversational Question Answering DatasetCode1
Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM InteractionsCode1
InCA: Rethinking In-Car Conversational System Assessment Leveraging Large Language Models—0
On the Robustness of Question Rewriting Systems to Questions of Varying HardnessCode0
Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources—0
GLaMM: Pixel Grounding Large Multimodal ModelCode2
EHRTutor: Enhancing Patient Understanding of Discharge Instructions—0
Strong and Efficient Baselines for Open Domain Conversational Question Answering—0
Robust Training for Conversational Question Answering Models with Reinforced Reformulation Generation—0
CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering—0
Prompt Guided Copy Mechanism for Conversational Question Answering—0
Learning to Select the Relevant History Turns in Conversational Question Answering—0
No that's not what I meant: Handling Third Position Repair in Conversational Question AnsweringCode0
DiPlomat: A Dialogue Dataset for Situated Pragmatic Reasoning—0
PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for FinanceCode2
Phrase Retrieval for Open-Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive LearningCode0
KL-Divergence Guided Temperature SamplingCode0
The Dangers of trusting Stochastic Parrots: Faithfulness and Trust in Open-domain Conversational Question Answering—0
Large Language Models Need Holistically Thought in Medical Conversational QACode0
Explainable Conversational Question Answering over Heterogeneous Sources via Iterative Graph Neural NetworksCode1
Keeping the Questions Conversational: Using Structured Representations to Resolve Dependency in Conversational Question Answering—0
Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty MeasurementCode0
Semantic Parsing for Conversational Question Answering over Knowledge GraphsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APOLLOExecution Accuracy78.76—Unverified