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Newest papers, page 240
Challenges of Multi-Speaker Extraction for Real Conversational Speech Enhancement
Target-speaker and multi-speaker extraction are techniques for extracting speech from a desired speaker or desired speakers in the presence of other speakers and/or noise.MICRO: Multi-Fidelity Active Search for Severe Error Discovery
Human feedback can vary in cost and informativeness.Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining
Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature.Truth for Believable AI: Expressed Doubt, Provenance, and Belief Revision as an Engineerable Stance
Conversational agents often express answers in a uniformly confident register.FIRE: Failure-Informed Runtime Engineering for Reliable Language-Model Agents
Language-model agents often reach a working solution and then fail to consistently deliver it.CHiME-9 ECHI: A Machine Learning Challenge for Enhancing Conversations to Address Hearing Impairment
This work presents the task and results of the CHiME-9 challenge for Enhancing Conversations to address Hearing Impairment.Designing and Analysing Argument Mining Pipelines: Towards a Comprehensive Assessment
Argument Mining (AM) transforms natural language into its underlying argument structures.Blaming Across the Aisle: Political Contrasting and Blame Attribution in the Danish Parliament
Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce.TransBERT: A Framework for Synthetic Translation in Domain-Specific Language Modeling
The scarcity of non-English language data in specialized domains significantly limits the development of effective Natural Language Processing (NLP) tools.HySparse2: Hybrid Sparse Attention with Two-Level KV Sharing
Long-horizon and multi-turn agents typically generate short actions and process long observations from tools and environments.Layout-Guided Masking for GROBID: Lightweight Structural Gains in Large-Scale Scientific PDF Ingestion
Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems.On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Quality
Recent advances in large language models (LLMs) have made them widely used for code-related tasks.Combining Hierarchical Cognitive Process with Process Supervision for Interpretable Scene Safety Understanding
Scene safety understanding plays a life-or-death role in situational awareness in various critical domains.Enriching Speech Emotion Representations with Conversational Context
Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans.How to Estimate Whether You Have Found Several Needles in a Haystack: Measuring Calibration in Multi-Label Text Classification
A key factor in deciding whether to trust an automatic prediction is its confidence score, which should be calibrated to match the actual probability of the prediction being correct.Behavior is Not Enough: A Mechanism-Based Evaluation of Social Norm Emergence in LLM Societies
Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simple imitation.Spoken Language Models that Think Aloud
While Chain-of-Thought (CoT) reasoning has improved the capability of language models, directly applying it to Spoken Language Models (SLMs) may introduce long silent intervals under the serial…Calibration as a First-Class Criterion in LLM Evaluation
Calibration of language models -- the alignment between expressed or implicit confidence and empirical correctness -- is a well-studied subfield within NLP.A Semiotics-Aware Framework for Evaluating Fidelity and Coverage in Natural Language Generation
When two texts describe the same expression, standard metrics based on lexical overlap or whole-text similarity may fail to detect meaningful differences in how that expression is framed.Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation
In LLM-based speech translation, transcription-based chain-of-thought (CoT) suffers from a mismatch between reference transcripts used in supervised fine-tuning (SFT) and model-generated transcripts…