Cool Papers · cs.CL (papers.cool) · RSS 摘要

信源：Cool Papers · cs.CL (papers.cool) · https://papers.cool/arxiv/cs.CL/feed

• Tracing the Scientific Discovery Capacity of LLMs to Their Training Data — Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery. How can we trace the scientific disco…
• ufakzeka-kulak: Building and Evaluating a 31.6M-Parameter Turkish Speech Recognizer from Scratch — ufakzeka-kulak is an open Turkish speech-to-text model of 31.6M parameters, a FastConformer encoder with a token-and-duration transducer (TDT) and a CTC head, trained from scratch…
• NitiBench+: A Temporal Thai Legal Question Answering Benchmark Across 17 Domains — Law changes over time. A court decides a case under the law in force on that day, and legal QA benchmarks grade answers against today's law. We checked 156,650 decisions of four T…
• VeriHarm-Bench: Measuring Harmful Success in LLM Coding Agents Verifiably — Large language model (LLM) coding agents increasingly operate with shell access, allowing them to write scripts, move files, alter permissions, and modify system configurations. H…
• Can LLM Agents Be Forward-Deployed Engineers? Requirement Discovery and Delivery for Enterprise Text-to-SQL — LLM coding agents can increasingly automate model post-training, but whether they can act as forward-deployed engineer (FDE) agents, discovering customer requirements and turning …