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Newest papers, page 147
The Persona Hierarchy Model: Understanding Contextual Generalization in Fine-Tuning LLMs
Language models are routinely fine-tuned under a fixed context, such as a generic system prompt, persona or domain-specific instruction, yet the learned behavior sometimes stays confined to that…ARCS: Towards Precise Text-to-SQL via Structured Disambiguation
As text-to-SQL systems move beyond demonstrations toward real-world deployment, ambiguity in user questions becomes a primary source of errors.Finding the Right Balance: Relevance and Diversity in LLM Retrieval
Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves retrieval and answer quality.Arctic Questions, Missing Answers: A Dataset and Benchmark for LLM Abstention in Arctic Science
Large language models (LLMs) should abstain from scientific multiple-choice questions when no option is valid, but frequent abstention alone does not demonstrate sensitivity to answer availability.Right Number, Wrong State? Measuring Cross-Jurisdiction Substitution in LLM Recall of State Policy
When an LLM answers a state-specific policy question wrongly, it may be hallucinating, or it may be returning a real value that holds in another state.BanglaRhet: Benchmarking Classical and Transformer Models for Rhetorical and Persuasion Detection in Bangla Political Speech
Political discourse often uses rhetorical and persuasive language to frame narratives, influence public opinion, and mobilize audiences.Boundary-Free Contextual Biasing: Depth-Adaptive Gating and Reading-Space Matching for Unsegmented Languages
Contextual biasing supplies an ASR system with a list of expected words at inference time, but existing methods rely on word boundaries that Japanese and Chinese do not provide.CHASE: Channel-Aligned Structure Exploitation for Geometry-Aware Model Engineering
Geometric and Spectral Alignment (GSA) characterizes trained networks through spectral concentration, physical-channel alignment, support structure, and changes in singular bases.Mitigating Accent-Language Confusion in Self-Supervised Speech Representations for Language Identification
Spoken language identification (LID) aims to recognize the target language regardless of accent.Goldsmith: Gold-Loss-Guided Definition Optimization with an Agentic Annotation Harness
Many annotation projects begin before experts have a stable guideline or enough labels to train a task-specific model.A Comparative Study of Evaluation Metrics for Long-Document Financial Narrative Summarization with Transformers
There are more than 2,000 listed companies on the UK's London Stock Exchange, divided into 11 sectors who are required to communicate their financial results at least twice in a single financial year.Certified by Abstention: Distribution-Free Guarantees for Chain-of-Thought Verifiers at Small Calibration Budgets
Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee.Constitution-Guided Watermarking
Watermarking enables language model providers to identify text generated by their models.RELATE: An Evaluation Framework for measuring Relational Orientation of Large Language Models
Large language models (LLMs) are increasingly used for emotional support, raising concern that sustained use may draw users away from their real-world relationships.How Do LLMs Change Predictions Under Negation?
Negation is an essential feature of human language, yet large language models (LLMs) remain unreliable in processing it.Collaborative Reasoning Distillation via Cross-Feedback and Coherent Curation
Reasoning capabilities are critical for advancing Large Language Models, yet current approaches either require massive computational budgets or struggle to effectively distill reasoning to smaller…Which Language Should a Skeleton Speak? Language Choices in Multilingual Reasoning
Skeleton-based reasoning prompting is a promising training-free approach for structuring LLM reasoning, but prior work largely assumes an English-centric setting.Coding-Agent Benchmarks Should Match Their Users' Task Flows
The evaluation of coding agents generally strives to be as realistic as possible.On-Policy Distillation Teaches New Skills but Not New Knowledge
On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-step reasoning remains unknown.When Rank Rises as LLMs Degrade
Post-training adapts language models in non-stationary environments.