Classical and neural NLP: translation, question answering, tokenization and the evaluation of language understanding.
arXiv:2607. 10491v1 Announce Type: new Abstract: Retrieval-augmented generation grounds large language models in external evidence, but most pipelines still treat retrieved passages as deterministic and mutually consistent context.
arXiv:2607. 11270v1 Announce Type: cross Abstract: Learning, at its core, extends beyond memorization to the ability to reason and solve novel problems by navigating a space of possibilities.
arXiv:2607. 11257v1 Announce Type: cross Abstract: Pathology Foundation Models (PFMs) offer powerful Whole Slide Image (WSI) representations but suffer from massive computational costs.
arXiv:2607. 11683v1 Announce Type: cross Abstract: Graph retrieval-augmented generation (GraphRAG) enhances large language models with structured knowledge, yet existing systems construct knowledge graphs in a single extraction pass, producing noisy entities and brittle retrieval.
arXiv:2607. 10825v1 Announce Type: cross Abstract: Opinionated text - spanning product reviews, hotel feedback, and social posts - captures rich signals about user experiences, preferences, and concerns.
arXiv:2607. 10562v1 Announce Type: new Abstract: Evaluating the multi-hop reasoning capabilities of large language models remains a significant challenge.
arXiv:2607. 09711v1 Announce Type: new Abstract: Existing agent benchmarks primarily test task completion, tool use, or skill utility, but do not isolate whether a runtime can convert evidence from its own runs into reusable skills that improve fresh executions after authoring overhead.
arXiv:2601. 15353v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has achieved remarkable success in real-world decision-making across diverse domains, including gaming, robotics, online advertising, public health, and natural language processing.
arXiv:2607. 10795v1 Announce Type: new Abstract: In open-domain multi-hop question answering (QA), LLM-based search agents offer a promising approach to knowledge-intensive QA by combining retrieval with reasoning.
arXiv:2607. 09712v1 Announce Type: new Abstract: Financial control testing increasingly depends on representative enterprise resource planning (ERP) data in quality environments, yet direct production copies expose personal, supplier, banking, and commercially sensitive records.
arXiv:2607. 09880v1 Announce Type: cross Abstract: Clinical time series are central to patient monitoring, risk assessment, and clinical decision support.
arXiv:2607. 09957v1 Announce Type: cross Abstract: This report studies on-device English-to-Traditional-Chinese subtitle translation for Taiwan under short inputs, short outputs, batch-size-one inference, low latency, and privacy constraints.
arXiv:2605. 17932v2 Announce Type: replace-cross Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations focus mainly on autoregressive architectures.
arXiv:2607. 10190v1 Announce Type: cross Abstract: Video-language models (VLMs) have achieved remarkable performance on video understanding and visual question answering, yet they remain unreliable in reasoning about physical plausibility, where understanding object interactions, causal dynamics, and fundamental physical principles is essential.
arXiv:2607. 09796v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) has become an important method for aligning large language models (LLMs) with human preferences because it removes the need for explicit reward modeling and reinforcement learning optimization.
arXiv:2607. 10588v1 Announce Type: new Abstract: Tasks such as customs tariff classification, export control categorization, and standards-based equipment coding require assigning an input instance to a fine-grained class under an explicit regulatory hierarchy.
arXiv:2606. 05494v3 Announce Type: replace-cross Abstract: Automatic text summarization has become increasingly important due to the rapid growth of digital textual information.
arXiv:2607. 10463v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) extends static RAG by allowing language models to iteratively reason, generate search queries, retrieve evidence, and predict answers.
arXiv:2607. 11487v1 Announce Type: cross Abstract: Personal AI assistants on mobile and wearable devices continuously perceive users' daily lives through visual and audio streams.
arXiv:2607. 11364v1 Announce Type: cross Abstract: Generating immersive, synchronized and cinematic audio for long-form textual narratives remains a significant challenge in multi-modal AI.