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Computation & Language / NLP
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Newest papers, page 34
Scaling Lean Theorem Proving for Real-World Code Verification
We present EasyProver, a Lean proving system built from recursive agents with isolated contexts, asynchronous search, parallel tactic probing, and an elastic elaboration service.Component Translation and Judge-Labelled Refusal: A Multilingual Safety Evaluation
Whole-prompt translation evaluates a request in different languages but does not compare which component carries a language.Two Birds with One Stone: Skill-Augmented Generation via Unified Retrieval and Utilization
Skills, as reusable external knowledge, have demonstrated substantial potential to enhance the ability of Large Language Models (LLMs) to solve complex tasks.3DCodeEdit: Benchmarking Instruction-Guided 3D Program Editing
Language models increasingly create 3D content through code, with practical workflows often relying on editing existing programs rather than regenerating them, for speed and precise control.Keepace.ai: A Technical Report on a Large Language Model for Sports and Health
Large language models hold promise for delivering safe, scientifically grounded, and personalized exercise guidance at scale, yet the sports-and-health domain still lacks curated training corpora…Cross Lingual Abstractive Summarization for Marathi
Text summarization is an important task for advancing natural language processing (NLP) research and applications in Indic languages.Human Evaluation with Automatic Scores: Separating Sampling and Estimation Gains
Automatic judges offer inexpensive information about model outputs, but an evaluation team must decide how to turn that information into fewer human annotations.EPSBench: Benchmarking LLM Agents for Earnings Forecasting
Quarterly earnings forecasting requires an agent to connect financial evidence to the income-statement line items that produce a company's reported earnings.Robust LLM-Generated Text Detection through Matched Conditional-Response Probing
Reliable detection of large language model (LLM)-generated text must remain effective under meaning-preserving text revisions, such as rewriting, polishing, and expansion.Fu-TCM: a multimodal large language model that learns traditional Chinese medicine diagnostic reasoning
Large language models (LLMs) are advancing in multimodal understanding and reasoning, accelerating medical model development.Statutory Article Retrieval from Arabic Judicial Narratives: Family Law and Law of Evidence in Saudi Arabia
Reliable legal information retrieval must ground legal reasoning in authoritative statutory sources.Manifest-Assisted Retrieval in Artificial Intelligence Search: Evidence Gaps and a Security Evaluation
The external sources retained in our non-systematic audit did not isolate the incremental security or utility effect of consuming /llms.txt while ordinary retrieval remained fixed.TCC-RAG: Temporal Causal Chain-Guided RAG for Temporal Knowledge Graph Question Answering
Recent advances in large language models (LLMs) have spurred growing interest in temporal knowledge graph question answering (TKGQA).How Much Do Teacher Bridges Matter in Interleaved On-Policy Distillation?
On-policy distillation (OPD) trains a student using teacher predictions on student-generated responses.Pronunciation-Supervised Text-to-Speech for Irish (Gaeilge)
Speech technology for Irish must be built from very little transcribed speech, yet the language's pronunciation is thoroughly documented in dictionaries and dialect descriptions.LLMs as Judges and Examinees for Medical Item Difficulty Prediction
Predicting medical item difficulty from item text alone remains challenging.Holistic Diversity Management in LLM-Guided Evolutionary Search
LLM-guided evolutionary search iteratively selects existing programs, uses LLMs as mutation operators to generate a new program, and evaluates it to guide subsequent search.Deeper Backpropagation or More Updates? Training Looped Language Models Across Budgets
Repeating transformer layers can improve language model performance without adding parameters.Does Chain-of-Thought Reliance Follow a Scaling Law?Larger Models Follow Their Steps More, Independent of Post-Training
Monitoring a model's chain of thought (CoT) is useful for safety only if the final answer depends on the written steps.RoleFUZZER: User-Behaviour Fuzzing for Role-Specification Adherence in Large Language Models
Large language models (LLMs) are often conditioned into specific roles such as tutors, interviewers, or agents acting for an organisation, through system prompts that specify how they should behave.