Papers Natural Language Understanding
“Natural Language Understanding” 태그가 달린 논문 2,181편 · 필터 해제
From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health
The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and privacy concerns, has created an urgent need for …
Natural Language UnderstandingLarge Language Models with At Most One Spike per Neuron
Leveraging their inherent sparse event-driven computation, spiking neural networks (SNNs) offer a promising path toward energy-efficient large language models (LLMs). Time-to-first-spike (TTFS) coding generates at most o…
Natural Language UnderstandingNL2AGBench: Benchmarking LLM Auto-Formalization for AlphaGeometry
Recent advances in large language models (LLMs) have demonstrated strong capabilities in natural language understanding and mathematical reasoning. However, their ability to translate informal mathematical problems into …
Natural Language UnderstandingMathematical ReasoningSymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers
Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reasoning, frequently suffering from hallucinations and inconsistency. Exi…
Natural Language UnderstandingLogical ReasoningLearning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation
We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting synthetic examples with a fixed reward threshold, our method formul…
Natural Language UnderstandingFact VerificationSPADE: Speculative Decoding for Precise and Low Cost Distributed Edge Cloud Inference
Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by high computational demands. Deploying smaller LLMs directly on the ed…
Natural Language UnderstandingInformation Abundance Paradox: Long-Context Training Undermines Parametric Knowledge
Large language models are increasingly trained and deployed with long contexts that span documents, code repositories, and interaction histories. This scaling reflects the implicit assumption that training on longer cont…
Natural Language UnderstandingA Heuristic Perspective on Debiasing Language Models
Language models (LMs) often acquire various biases during pre-training and may express them in interactions, potentially causing social harm. Existing methods often rely on counterfactual augmentation or representation p…
Natural Language UnderstandingEuclid-MCP: A Model Context Protocol Server for Deterministic Logical Reasoning via Prolog
Large Language Models (LLMs) excel at natural language understanding and generation but remain unreliable for multi-step logical reasoning, especially in safety-critical or compliance-sensitive domains. Recent neuro-symb…
Natural Language UnderstandingLogical ReasoningStatistical Inference for Rank Allocation in Low-Rank Adaptation
Low-rank adaptation (LoRA) has become a widely used parameter-efficient fine-tuning method for large language models. Since different modules and layers may contribute unequally to downstream adaptation, allocating rank …
parameter-efficient fine-tuningNatural Language UnderstandingQuestion AnsweringMetaHOPE: A Metaphor-Oriented Evaluation Framework for Analysing MT and LLM Translation Errors
In this opinion paper, we propose MetaHOPE, an error severity-aware annotation framework for evaluating metaphor translations. Metaphors present challenges for machine translation (MT) and natural language understanding …
Natural Language UnderstandingMachine TranslationCharacterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem
Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combine natural language understanding with external services and APIs. LL…
Natural Language UnderstandingDziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect
Automatic speech and language technologies are still heavily biased toward high-resource languages, limiting their applicability to dialectal and low-resource settings such as Algerian Dialect. This language presents add…
Natural Language UnderstandingText-To-Speech SynthesisIntent ClassificationResponse GenerationVisChronos: Revolutionizing Image Captioning Through Real-Life Events
This paper aims to bridge the semantic gap between visual content and natural language understanding by leveraging historical events in the real world as a source of knowledge for caption generation. We propose VisChrono…
Natural Language UnderstandingDense CaptioningImage CaptioningmoBERTo: A Modern Encoder for Portuguese via Continued Pretraining of ModernBERT
Encoder-only transformer models remain essential for production NLP pipelines. We introduce moBERTo, a Portuguese adaptation of ModernBERT obtained through continued pretraining of the ModernBERT-base checkpoint on 60 bi…
Natural Language UnderstandingDocument ClassificationInformation RetrievalPragReST: Self-Reinforcing Counterfactual Reasoning for Pragmatic Language Understanding
Natural language understanding often depends on meanings that are implied rather than explicitly stated, requiring pragmatic reasoning. Despite strong performance on math and logical reasoning, large language models (LLM…
Natural Language UnderstandingReinforcement LearningMathematical ReasoningLogical ReasoningChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing
Personalized public transit routing in public transit systems remains challenging due to the difficulty of capturing and integrating diverse user preferences into routing algorithms. This paper presents ChatPlanner, a no…
Natural Language UnderstandingNatural Language QueriesInformation ExtractionA Multi-Agent AI System for Automated High School Transcript Processing: Collaborative Document Analysis at Scale
Each year, college admissions offices face an overwhelming challenge: processing millions of high school transcripts, each with unique formats, grading systems, and layouts. This manual process creates operational bottle…
Natural Language UnderstandingCaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
Existing calibration methods for Large Language Models (LLMs) often overlook a critical dimension of trustworthiness: a model's {\em behavioral robustness} to irrelevant or misleading information. In this paper, we argue…
Natural Language UnderstandingModular Monolingual Adaptation using Pretrained Language Models
Building monolingual language models (LMs) for low-resource languages typically relies on adapting pretrained language models (PLMs) by finetuning the whole model on the target language. This approach is widely favored o…
Natural Language Understanding