This paper proposes a framework for summarizing dialogues, modeling semantic and emotion dynamics using multimodal inputs and an adapted hierarchical Chain-of-Agents approach.

The paper introduces Dialogs, a new Russian conversational speech corpus with high-quality recordings, segmented utterances, and expressive prosody labels.

TalTech submitted top-ranking systems to the Beyond Transcription Challenge using fine-tuned Voxtral models and reinforcement learning against Open Medical Concept F1.

This paper proposes a scalable framework for multi-domain dialogue state tracking using pretrained BERT model for zero-shot generalization.

This paper investigates how the final prompt in conversational AI-search evaluations differs from the conversation history, using two corpora of commercial and PRISM conversations.

This paper proposes a multi-turn retrieval-augmented generation pipeline for conversational systems across four domains.

The paper introduces BEA-Dialogue+, an expanded 200-hour corpus for Hungarian conversational ASR, demonstrating that while larger data is challenging, specialized fine-tuning techniques significantly…

CobSeg introduces a multi-branch architecture that enhances dialogue topic segmentation by explicitly modeling both semantic coherence and local lexical boundary transitions, achieving state-of-the-ar…

The paper introduces TikStance, a multimodal and context-aware dataset for stance detection in political discussions on TikTok.

The paper introduces a new benchmark for multi-target cross-lingual summarization (MTXLS) and proposes an activation steering method that significantly improves LLM performance by guiding the generati…

This paper explores the effect of conversational timing properties on automatic speech recognition (ASR) systems by controlling and optimizing pause and overlap timing distributions.

This paper introduces model merging as a training-free strategy for designing a single retrieval model that operates across both ad-hoc and conversational settings, improving ad-hoc search capabilitie…

The paper introduces a supervised fine-tuning pipeline using large language models to accurately categorize sentence-level clinical provenance across multi-disciplinary hospital notes, demonstrating t…

The paper introduces SPEARBench, a benchmark for evaluating naturalness in speech-to-speech language models using a multidimensional protocol.

This paper proposes Efficient Chain-of-Modality Reasoning (ECoM Reasoning), a framework to improve reasoning ability in spoken language models (SLMs) for mathematical question answering tasks by compr…

This paper proposes conversational AI review assistants for code review, systems that engage in conversation with developers instead of just generating comments.

This paper introduces the Goal-Oriented Dialogue Runtime (GODR), a framework-neutral design pattern for managing complex, multi-domain, interruptible conversations with multiple interdependent objecti…

The paper demonstrates 'argument collapse,' showing that LLMs tend to converge on a small, repetitive set of polished arguments when generating long-form public debates, significantly reducing the div…

The Cologne Information Retrieval group participated in iKAT SCAI 2026 shared task using an agentic conversational search system with query rewriting, retrieval, reranking, answer generation, and clar…