Answer Selection
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Benchmarks
Most implemented
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems
Neural Variational Inference for Text Processing
Gated-Attention Readers for Text Comprehension
Simple and Effective Text Matching with Richer Alignment Features
Papers
Tracing Audio Grounding and Answer Selection in Audio LLMs
Audio Large Language Models (Audio LLMs) have advanced in audio understanding, yet they can still predict the answer by reasoning from textual cues or linguistic priors rather than the provided audio. A common remedy is …
Answer SelectionCandidate supply and answer selection shape the value of LLM judging in multi-agent systems
Multi-agent systems (MAS) sometimes already have the potential to answer correctly, but still report a wrong answer. Explaining this outcome is difficult because generation, communication and final answer-selection rules…
Answer SelectionDirEAG: Dirichlet Evidence Aggregation for Calibrating Verbalized Confidence in Mathematical Reasoning
Reliable confidence estimation is essential for using large language models in mathematical reasoning, but black-box verbalized confidence is difficult to calibrate. When the same problem is queried under multiple confid…
Mathematical ReasoningAnswer SelectionAre You Sure You're Sure? On the Impact of Instruction Tuning on Confidence and Lexical Diversity
Instruction-tuned language models achieve strong performance across a range of generation tasks, but have also recently been shown to exhibit verbalized overconfidence. In question answering, verbalized model overconfide…
Question AnsweringAnswer SelectionLODESTAR: Robust Entropy-Based Answer Selection in Retrieval-Augmented Generation for Question Answering -- Directing Frozen-LLM Entropy with a Reinforcement-Learned Prompt Polarizer under Misleading Passages
Predictive-distribution entropy is a strong answer-selection rule in retrieval-augmented generation (RAG) for question answering: across five QA benchmarks, selecting the answer a frozen respondent LLM produces with the …
Reinforcement LearningQuestion AnsweringAnswer SelectionDetecting Hallucinations and Recovering Verified Answers in Arabic Islamic Question Answering
Large language models can generate fluent responses to Islamic questions while introducing factual errors that are difficult to identify. This paper presents our system for \textsc{HalluScoring 2026} Task 2.1, \textit{Is…
Question AnsweringAnswer Selection