News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — Machine Learning research 4d ago Stochastic Gradient Optimization with Model-Assisted Sampling arXiv:2606.27171v1 Announce Type: new Abstract: This work addresses the problem of variance in stochastic gradient estimation for machine learning optimization. Deep learning relies on mini-batch methods such as stochastic gradient descent, which approximate full gradients but… 34 arXiv — Machine Learning research 4d ago RecallRisk-BERT: A Multi-Task Framework for Post-Report Medical Device Recall Triage arXiv:2606.27174v1 Announce Type: new Abstract: Medical device recalls are a critical regulatory mechanism for protecting patient safety. The growing volume of FDA recall records presents challenges in post-report recall triage, severity assessment, and root-cause… 24 arXiv — Machine Learning research 4d ago Automating Potential-based Reward Shaping with Vision Language Model Guidance arXiv:2606.27180v1 Announce Type: new Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly attribute the sparse success rewards to relevant parts of the trajectory. Naive… 36 arXiv — Machine Learning research 4d ago Explaining Temporal Graph Neural Networks via Feature-induced Information Flow arXiv:2606.27201v1 Announce Type: new Abstract: Event-based Temporal Graph Neural Networks (ETGNNs) have demonstrated strong performance across a wide range of applications, including social network analysis, epidemic tracing, recommender systems, and political event… 5 arXiv — Machine Learning research 4d ago Graph Neural Networks Applications Across Domains: All Insights You Need arXiv:2606.27202v1 Announce Type: new Abstract: Graph neural networks have moved from a niche representation-learning technique to the default model class wherever data carry relational structure. The interesting question is no longer whether message passing helps on a given… 17 arXiv — NLP / Computation & Language research 4d ago The Geometry of Updates: Fisher Alignment at Vocabulary Scale arXiv:2606.27242v1 Announce Type: cross Abstract: Training-free source selection for LLM families with shared vocabularies arises in scientific string domains such as SMILES, protein, and genomic sequences, where candidate corpora share a tokenizer but differ in prediction… 38 arXiv — Machine Learning research 4d ago Effective Covariance Dynamics in Solvable High-Dimensional GANs arXiv:2606.27246v1 Announce Type: new Abstract: We study a solvable high-dimensional model of generative adversarial network (GAN) training in which a linear generator learns a low-dimensional subspace from data with structured latent covariance. Prior solvable GAN analyses… 33 arXiv — Machine Learning research 4d ago RSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist Annotations arXiv:2606.27247v1 Announce Type: new Abstract: In NLP, mental health conditions are often modeled as isolated phenomena, without interpersonal context. We use Reddit posts about long-distance relationships to capture both mental health distress and associated relational… 24 arXiv — Machine Learning research 4d ago BetXplain: An Explanation-Annotated Dataset for Detecting Manipulative Betting Advertisements on Social Media arXiv:2606.27274v1 Announce Type: new Abstract: The promotion of betting applications on social media platforms has increased significantly in recent years. Many of these advertisements use persuasive techniques that may mislead users, encourage risky behavior, and potentially… 37 arXiv — Machine Learning research 4d ago How Good Can Linear Models Be for Time-Series Forecasting? arXiv:2606.27282v1 Announce Type: new Abstract: Time-series forecasting research has been moving steadily toward larger architectures, from specialized transformers to general-purpose foundation models, on the assumption that capacity is what unlocks accuracy. We take the… 19 arXiv — Machine Learning research 4d ago Recovering Governing Equations from Solution Data: Identifiability Bounds for Linear and Nonlinear ODEs arXiv:2606.27285v1 Announce Type: new Abstract: Learning governing equations from observed solution data is a fundamental challenge in scientific machine learning… 15 arXiv — Machine Learning research 4d ago Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search arXiv:2606.27291v1 Announce Type: new Abstract: Job-search platforms rely on low-bandwidth query interfaces that often fail to capture the high-dimensional complexity of candidate profiles. We present an end-to-end RLAIF (Reinforcement Learning from AI Feedback) framework to… 10 arXiv — Machine Learning research 4d ago A Multi-Fidelity Convolutional Autoencoder-Transfer Learning Framework for Guided-Wave-Based Damage Diagnosis Using Large Simulated and Limited Experimental Datasets arXiv:2606.27304v1 Announce Type: new Abstract: Guided wave-based structural health monitoring (GWSHM) with onboard transducers offers significant potential for the early diagnosis of damage in engineering structures. However, the practical deployment of deep learning models is… 4 arXiv — Machine Learning research 4d ago Blackwell Approachability and Gradient Equilibrium are Equivalent arXiv:2606.27315v1 Announce Type: new Abstract: Gradient equilibrium (GEQ) is a recently introduced online optimization framework that generalizes first-order stationarity from offline optimization and abstracts problems like online conformal prediction. While GEQ has curious… 20 arXiv — Machine Learning research 4d ago Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders arXiv:2606.27321v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) have become a leading tool for interpreting the representations of vision foundation models, decomposing their polysemantic activations into a larger set of sparse, more monosemantic features. The Top-$k$… 22 arXiv — Machine Learning research 4d ago Hallucination in World Models is Predictable and Preventable arXiv:2606.27326v1 Announce Type: new Abstract: Modern generative world models render increasingly realistic action-controllable futures, yet they frequently hallucinate: rollouts remain visually fluent while drifting from the ground-truth dynamics. We hypothesize that… 19 arXiv — Machine Learning research 4d ago Error-Conditioned Neural Solvers arXiv:2606.27354v1 Announce Type: new Abstract: Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical task: once trained, they struggle to correct their own constraint violations and… 25 arXiv — Machine Learning research 4d ago Autoregressive Boltzmann Generators arXiv:2606.27361v1 Announce Type: new Abstract: Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics. This challenge has driven the development of Boltzmann Generators (BGs), which allow rapid generation of… 7 arXiv — Machine Learning research 4d ago Reinforcement Learning without Ground-Truth Solutions can Improve LLMs arXiv:2606.27369v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) for training LLMs typically rely on ground-truth answers to assign rewards, limiting their applicability to tasks where the ground-truth solution is unknown. We introduce a… 19 arXiv — NLP / Computation & Language research 4d ago Context Recycling for Long-Horizon LLM Inference arXiv:2606.26105v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong capabilities in short-context reasoning but degrade in performance over long conversational horizons due to context window limitations and inefficient token usage. We introduce… 27 arXiv — Machine Learning research 4d ago The Open Source Economic Index of AI Adoption and Capability arXiv:2606.26118v1 Announce Type: cross Abstract: We work towards measuring both AI adoption and the capability of AI to perform discrete labor tasks across various occupations. To measure adoption, we develop an open-source economic index that uses publicly available user-LLM… 5 arXiv — NLP / Computation & Language research 4d ago Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM arXiv:2606.26120v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirectional attention mechanisms. However, their computational complexity scales on… 15 arXiv — Machine Learning research 4d ago Dot-Flik: A Scalable Edge AI Architecture for Distributed Insect Monitoring arXiv:2606.26121v1 Announce Type: cross Abstract: Global insect population declines necessitate scalable, continuous monitoring systems, yet existing vision-based solutions remain constrained by high hardware costs, energy demands, and reliance on centralized processing or cloud… 11 arXiv — Machine Learning research 4d ago Code evolution for link prediction in complex networks arXiv:2606.26132v1 Announce Type: cross Abstract: The problem of predicting links in complex networks appears in different disciplines and has led to a variety of ingenious human-designed methods. We use this rich program space to explore the performance and behavior of… 8 arXiv — NLP / Computation & Language research 4d ago HierBias: Context-Conditioned Hierarchical Media Bias Detection with Multi-Task Type Classification arXiv:2606.26100v1 Announce Type: new Abstract: Media bias detection is a critical task for ensuring fair and balanced information dissemination, yet existing sentence-level approaches classify each sentence independently, ignoring inter-sentence contextual signals that human… 17 arXiv — NLP / Computation & Language research 4d ago Know2Guess: A Contamination-Aware Multi-Zone Benchmark for Knowledge-Boundary Evaluation in Large Language Models arXiv:2606.26101v1 Announce Type: new Abstract: Reliable evaluation of large language models should separate supported answering from unsupported guessing without conflating either with data contamination, prompt idiosyncrasy, or generic refusal behavior. We present a… 21 arXiv — NLP / Computation & Language research 4d ago Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training arXiv:2606.26102v1 Announce Type: new Abstract: Standard post-training pipelines apply supervised fine-tuning (SFT) and reinforcement learning (RL) to make language models helpful, but these processes may inadvertently degrade values instilled during pre-training. We investigate… 22 arXiv — NLP / Computation & Language research 4d ago Investigating LLM's Problem Solving Capability -- a Study on Statics Questions arXiv:2606.26103v1 Announce Type: new Abstract: Large Language Models (LLMs) have rapidly influenced many aspects of society, particularly education, due to their demonstrated ability to complete assignments and examinations across a wide range of subjects. Although prior… 35 arXiv — NLP / Computation & Language research 4d ago Assert, don't describe: Linguistic features that shift LLM reasoning about animal welfare arXiv:2606.26104v1 Announce Type: new Abstract: Animal-welfare advocates produce a lot of writing, and increasingly that writing trains the language models that millions of people then ask about animal welfare. Using vocabulary-matched stance-contrast probes on a held-out… 19 arXiv — NLP / Computation & Language research 4d ago Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints arXiv:2606.26106v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in emotionally charged situations involving interpersonal conflict, frustration, and distress. While prior safety research has focused on preventing explicit harms such as toxic or… 26 arXiv — NLP / Computation & Language research 4d ago Low Resource Multimodal Translation of Nepali Spoken Words into Emotion-Conditioned Sign Language Avatars arXiv:2606.26107v1 Announce Type: new Abstract: Sign language communication systems, that integrate emotional expression remain underexplored, particularly for low-resource languages. This pilot study presents NEST-V1 (Nepali Emotion and Speech Transformer - Version 1), a… 37 arXiv — NLP / Computation & Language research 4d ago Where Larger Models Excel: The Primacy of Constraint-Guided Reasoning arXiv:2606.26108v1 Announce Type: new Abstract: Larger language models consistently outperform smaller ones on reasoning benchmarks, yet the reasoning differences underlying this gap remain underexplored. Across benchmarks in mathematics, physics, chemistry, and programming, we… 35 arXiv — NLP / Computation & Language research 4d ago From Lexicon to AI: A Structured-Data Pipeline for Specialized Conversational Systems in Low-Resource Languages arXiv:2606.26112v1 Announce Type: new Abstract: Low-resource languages face a critical challenge in AI development: creating specialized conversational systems without access to massive training corpora. We present a systematic methodology for transforming structured linguistic… 36 arXiv — NLP / Computation & Language research 4d ago Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods arXiv:2606.26130v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting remain unclear. Here, we prompt GPT-5.1, Gemini 3 Pro, and DeepSeek-V3.2 with an… 38 arXiv — NLP / Computation & Language research 4d ago From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models arXiv:2606.26196v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have recently made remarkable progress in unifying vision-language understanding and reasoning, especially following the introduction of models such as OpenAI's O-series and DeepSeek's… 12 arXiv — NLP / Computation & Language research 4d ago Phonetic and semantic analyses of spoken corpora of Beijing and Taiwan Mandarin indicate that the neutral tone is a lexical tone arXiv:2606.26360v1 Announce Type: new Abstract: The neutral, or floating, tone of Mandarin Chinese is a tone with an enigmatic set of properties. It has been described as a reduced tone, or as a tone that sometimes is lexically fixed but that can also be toneless. In… 4 arXiv — NLP / Computation & Language research 4d ago Charting the Growth of Social-Physical HRI (spHRI): A Systematic Review Pipeline Augmented by Small Language Models arXiv:2606.26382v1 Announce Type: new Abstract: Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Yet, fragmented terminology and inconsistent methodologies make systematic… 35 arXiv — NLP / Computation & Language research 4d ago ProfileFoundry: A Synthetic Person-Object Substrate for Privacy, Memory, and Tool-Use Evaluation in LLM Agent arXiv:2606.26403v1 Announce Type: new Abstract: Foundation-model research increasingly needs data about people: user state, personal histories, relationships, contact-like fields, documents, and longitudinal updates. Real user data is difficult to share, perturb, audit, or… 34 arXiv — NLP / Computation & Language research 4d ago ConflictScore: Identifying and Measuring How Language Models Handle Conflicting Evidence arXiv:2606.26437v1 Announce Type: new Abstract: Existing metrics for factuality and faithfulness evaluate whether an answer is supported or contradicted by its grounding documents, but they fail to capture when both supporting and contradicting evidence coexist. We introduce… 6 arXiv — NLP / Computation & Language research 4d ago ProvenAI: Provenance-Native Traces of Evidence in Generated Answers arXiv:2606.26449v1 Announce Type: new Abstract: Retrieval-augmented systems routinely present citations alongside generated answers, yet a citation does not confirm that the corresponding source meaningfully shaped the output. This paper introduces ProvenAI, a framework that… 17 arXiv — NLP / Computation & Language research 4d ago AnySimLite: A Lightweight Few-Shot Similarity Encoder for On-Device Speech-Adjacent Classification arXiv:2606.26452v1 Announce Type: new Abstract: To minimize privacy concerns and inference latency on edge devices like smartphones, lightweight on-device models remain important for end-user applications. Many of these applications involve natural language classification, but… 31 arXiv — NLP / Computation & Language research 4d ago Soft Token Alignment for Cross-Lingual Reasoning arXiv:2606.26466v1 Announce Type: new Abstract: Multilingual large language models often produce inconsistent reasoning and answers for semantically equivalent prompts in different languages. Prior work suggests that intermediate representations can be relatively… 5 arXiv — NLP / Computation & Language research 4d ago Extracting Problem and Method Sentence from Scientific Papers: A Context-enhanced Transformer Using Formulaic Expression Desensitization arXiv:2606.26481v1 Announce Type: new Abstract: Billions of scientific papers lead to the need to identify essential parts from the massive text. Scientific research is an activity from putting forward problems to using methods. To learn the main idea from scientific papers, we… 24 arXiv — NLP / Computation & Language research 4d ago Utilizing Cognitive Signals Generated during Human Reading to Enhance Keyphrase Extraction from Microblogs arXiv:2606.26485v1 Announce Type: new Abstract: Microblogging platforms generate massive amounts of short, noisy, and dispersed user content, making automatic keyphrase extraction (AKE) an important but challenging task. Prior studies have used eye-tracking signals to improve… 7 arXiv — NLP / Computation & Language research 4d ago Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting arXiv:2606.26487v1 Announce Type: new Abstract: Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet their discrete, language-oriented tokenization and embedding interfaces are… 21 arXiv — NLP / Computation & Language research 4d ago Comparing BERT Sentence-Pair Classification and Few-Shot LLM Prompting for Detecting Threat and Solution Framing in German Climate News arXiv:2606.26489v1 Announce Type: new Abstract: News media play a central role in shaping public perceptions of climate change, and whether coverage emphasizes threats or solutions has measurable effects on audience engagement and policy support. Automated detection of these… 23 arXiv — NLP / Computation & Language research 4d ago Nemotron-TwoTower: Diffusion Language Modeling with Pretrained Autoregressive Context arXiv:2606.26493v1 Announce Type: new Abstract: Diffusion language models offer a promising alternative to autoregressive models due to their potential for parallel and iterative generation. However, existing approaches use a single network for both context representation and… 23 arXiv — NLP / Computation & Language research 4d ago Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge arXiv:2606.26511v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) gives agents access to accumulated knowledge, but has no model of time. When a fact changes (e.g., a function is renamed or API restructured), RAG retrieves both the stale and current value with… 6 arXiv — NLP / Computation & Language research 4d ago Assessing Post-Reform Changes in Risk Disclosure Quality with a Multidimensional Text Analysis Approach arXiv:2606.26522v1 Announce Type: new Abstract: While corporate narrative disclosures provide crucial information to capital markets, comprehensively evaluating their qualitative changes over time remains challenging. Narrative text is inherently multidimensional, meaning that… 27 arXiv — NLP / Computation & Language research 4d ago The Inattentional Gap: Task-Conditioned Language and Vision Models Omit the Safety-Critical Signals They Can Otherwise Report arXiv:2606.26529v1 Announce Type: new Abstract: AI safety is evaluated by how reliably a model detects the hazards it is told to find, yet accidents often arise from the hazard no one specified. We show that conditioning a language or vision model on a narrow task suppresses its… 14 Page 10 of 10 · 500 articles ← Newer
