News / #funding Tag Funding 500 articles archived under #funding · RSS Sign in to follow arXiv — NLP / Computation & Language research 1mo ago Deceptive Grounding: Entity Attribution Failure in Clinical Retrieval-Augmented Generation arXiv:2607.09349v1 Announce Type: new Abstract: Retrieval-augmented generation evaluation checks whether model claims are factually grounded in retrieved documents. It does not check whether retrieved evidence is attributed to the correct entity. A clinical RAG response can pass… 38 arXiv — NLP / Computation & Language research 1mo ago Decoupling Task-Solving and Output Formatting in LLM Generation arXiv:2510.03595v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly adept at solving complex problems, such as mathematical reasoning and automatic evaluation. However, performance often degrades when prompts intertwine task instructions with rigid… 27 arXiv — NLP / Computation & Language research 1mo ago Probabilistic Textual Time Series Depression Detection arXiv:2511.04476v2 Announce Type: replace Abstract: Accurate and interpretable predictions of depression severity are essential for clinical decision support, yet existing models often lack uncertainty estimates and temporal interpretability. We propose PTTSD, a Probabilistic… 16 r/LocalLLaMA community 1mo ago **Your $80 Tesla P100 has been doing silently noisy math in llama.cpp for years. Three lines fix it, for free.** ## TLDR; Shipped — in turboquant v0.3.0, downloadable now. https://github.com/TheTom/llama-cpp-turboquant/releases/tag/tqp-v0.3.0 llama.cpp's CUDA code has a flag that means "this GPU is fast at fp16, so do the math in fp16." The GTX 10-series and P40's (sm_61) were exempted… 7 r/LocalLLaMA community 1mo ago Literature Review: MELTing point: Mobile Evaluation of Language Transformers | Bnechmarking LLMs on Phones Finished reading the paper: MELTing point: Mobile Evaluation of Language Transformers I am starting to benchmark LLMs on edge devices, particularly phones thus been reading a lot on the what has been done and what is currently being done and wanted to share you my journey of… 22 Smol AI News news-outlet 1mo ago not much happened today **Prime Intellect** released **verifiers v1**, a redesigned environment stack for **agentic reinforcement learning** and evaluations, improving efficiency by storing rollout traces as **message DAGs** to reduce complexity from **O(n²)** to **O(n)**. This enables practical… 29 Hugging Face Daily Papers research 1mo ago UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks Abstract UniClawBench introduces a capability-driven benchmark for evaluating proactive agents in real-world environments using live Docker container evaluation and closed-loop assessment with multiple agent roles. Generated by Qwen/Qwen2.5-Coder-32B-Instruct The rapid… 26 Hugging Face Daily Papers research 1mo ago Video-Oasis: Rethinking Evaluation of Video Understanding Abstract Video-Oasis diagnostics reveal that half of existing video benchmarks can be solved without visual input, exposing significant capability gaps in current video understanding models. Generated by Qwen/Qwen2.5-Coder-32B-Instruct The inherent complexity of video… 29 arXiv — Machine Learning research 1mo ago Principled Analysis of Deep Reinforcement Learning Evaluation and Design Paradigms arXiv:2607.07769v1 Announce Type: new Abstract: Starting from the utilization of deep neural networks to approximate the state-action value function that led to winning one of the most challenging games, to algorithmic advancements that allowed solving problems without even… 21 arXiv — Machine Learning research 1mo ago Physics-Informed Machine Learning Under Small-Data Constraints: Lessons from Abrasive Waterjet Milling arXiv:2607.07863v1 Announce Type: new Abstract: In physically dominated machining processes, experimental datasets are small, expensive, and material-specific; in this regime, data curation, evaluation design, and the form of physics integration can matter as much as the… 35 arXiv — Machine Learning research 1mo ago Certified Interventional Fidelity: Anytime-Valid, Adaptive Evaluation of Causal Claims in Mechanistic Interpretability arXiv:2607.08349v1 Announce Type: new Abstract: Mechanistic interpretability often evaluates explanations by intervening on a model: swapping hidden states, patching activations, ablating components, or comparing a compressed model to the original one. These experiments are… 15 arXiv — Machine Learning research 1mo ago Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles arXiv:2607.08373v1 Announce Type: new Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from normal operation before they propagate into failures. Such evaluation is challenging… 32 arXiv — Machine Learning research 1mo ago Predicting Male Fertility Using Machine Learning: A Semen Parameters Based Analysis with the VISEM Dataset arXiv:2607.08429v1 Announce Type: new Abstract: Male infertility is a significant yet often underdiagnosed aspect of reproductive health, with semen analysis serving as the cornerstone of clinical evaluation. To address this problem, this study investigates the use of machine… 8 arXiv — Machine Learning research 1mo ago Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures arXiv:2607.08511v1 Announce Type: new Abstract: Choosing a learning rate scheduling strategy is critical to neural network training, but manual selection is costly and rarely exhaustive. While classical AutoML approaches often treat the scheduler as a secondary hyperparameter,… 30 arXiv — Machine Learning research 1mo ago Stop Guessing When to Stop Testing: Efficient Model Evaluation with Just Enough Data arXiv:2607.08522v1 Announce Type: new Abstract: The inherent rigidity of fixed-size benchmarks makes them an inefficient tool for model evaluation. Diverse evaluation objectives, including model ranking, model selection and testing throughout development, demand varying levels… 26 arXiv — Machine Learning research 1mo ago CAAD: Causality-Aware Multivariate Time Series Anomaly Detection via Multi-Scale Alignment and Structural Causal Consistency arXiv:2607.08555v1 Announce Type: new Abstract: The operational integrity of complex industrial systems relies on precise anomaly detection and diagnosis. The vast majority of existing methods narrowly focus on capturing temporal similarities of representations, often… 12 arXiv — NLP / Computation & Language research 1mo ago Best-of-$N$ TTS Evaluation is Confounded by ASR Family Alignment arXiv:2607.08256v1 Announce Type: new Abstract: Best-of-$N$ (BoN) inference improves content consistency in zero-shot text-to-speech by selecting from $N$ candidates with an automatic speech recognition (ASR) verifier. We identify an underexplored evaluation confound: a… 18 arXiv — NLP / Computation & Language research 1mo ago The Memory Wall of Green Software: Empirical Energy Evaluation of Memento Design Pattern arXiv:2607.07944v1 Announce Type: cross Abstract: As Green Software Engineering matures, energy efficiency has transitioned into a mission-critical non-functional requirement. While software design patterns ensure structural integrity, their inherent abstraction layers impose an… 5 arXiv — NLP / Computation & Language research 1mo ago The complexities of patient-centred conversational artificial intelligence arXiv:2607.08625v1 Announce Type: cross Abstract: Consumer-facing health chatbots powered by large language models (LLMs) are increasingly used for symptom assessment. However, chatbot development and evaluation often rely on cooperative, articulate, simulated patients. We… 22 arXiv — NLP / Computation & Language research 1mo ago Fair Document Valuation in LLM Summaries via Shapley Values arXiv:2505.23842v5 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly power search engines and AI assistants that retrieve and summarize content from many sources. By serving answers directly, these systems obscure the original content creators'… 10 arXiv — NLP / Computation & Language research 1mo ago DR-Arena: an Automated Evaluation Framework for Deep Research Agents arXiv:2601.10504v2 Announce Type: replace Abstract: As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, reliable evaluation of their task performance has become a critical bottleneck.… 33 arXiv — NLP / Computation & Language research 1mo ago An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation arXiv:2602.13376v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly used in document processing pipelines to convert flowchart images into structured code (e.g., Mermaid). In production, these systems process arbitrary inputs for which no… 21 Simon Willison community 1mo ago Introducing Muse Spark 1.1 Introducing Muse Spark 1.1 Following Muse Spark in April , here's Muse Spark 1.1 - the first Spark model to offer an API. Meta claim significant improvements in agentic tool calling and computer use. There are a lot more details are in the Muse Spark 1.1 Evaluation Report . The… 27 Hugging Face Daily Papers research 1mo ago AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation Abstract We present AgentLens, a production-assessed benchmark for interactive code agents. Most code-agent benchmarks reduce a run to a single bit -- did the task pass? -- but the people who actually use these agents experience the entire trajectory: how the agent follows… 34 arXiv — Machine Learning research 1mo ago Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia arXiv:2607.06626v1 Announce Type: new Abstract: Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask whether this alignment extends to reward valuation, which we assess in a mechanistic framework built on clinical tests that were… 32 arXiv — Machine Learning research 1mo ago Enhancing deep learning models for time series classification via knowledge distillation arXiv:2607.06796v1 Announce Type: new Abstract: Deep learning has achieved remarkable success in various domains including time series analysis, computer vision and natural language processing. However, high computational and memory demands of state-of-the-art architectures pose… 26 arXiv — Machine Learning research 1mo ago LEMUR 2: Unlocking Neural Network Diversity for AI arXiv:2607.06839v1 Announce Type: new Abstract: Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain or deployment-aware evaluation. LEMUR 2 introduces a large-scale, extensible… 22 arXiv — Machine Learning research 1mo ago Rethinking Multimodal Time-Series Forecasting Evaluation arXiv:2607.06973v1 Announce Type: new Abstract: We introduce a new context-enriched, multimodal time series forecasting benchmark, TimesX. TimesX contains a wide selection of high-quality real-world time series with diverse domains and textual contexts obtained from an automated… 24 arXiv — Machine Learning research 1mo ago Prior-matched evaluation of operational Earth-observation classifiers: a three-number reporting method demonstrated on Sentinel-1 internal-wave detection arXiv:2607.07146v1 Announce Type: new Abstract: The Internal Waves Service screens the Sentinel-1 Wave-mode archive for internal solitary waves, routing detections to experts whose adjudication time is the resource the effort exists to conserve. Because attention is the cost of… 29 arXiv — Machine Learning research 1mo ago Predicting LLM Safety Before Release by Simulating Deployment arXiv:2607.07184v1 Announce Type: new Abstract: Pre-deployment safety evaluations aim to inform the downstream risks of releasing a new AI model. Yet most evaluations provide limited evidence about how often undesired model behavior will occur in deployment: they generally have… 31 arXiv — Machine Learning research 1mo ago FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series arXiv:2607.07258v1 Announce Type: new Abstract: In many realistic scenarios, large volumes of time series data are generated with limited or expensive annotations. This limitation makes supervised learning methods difficult to apply and leads to the use of unsupervised… 25 arXiv — Machine Learning research 1mo ago TimEE: End-to-end Time Series Classification via In-Context Learning arXiv:2607.07500v1 Announce Type: new Abstract: Time series classification (TSC) is dominated by a two-stage paradigm: train a feature encoder -- either from scratch on the target dataset or via pretraining on large corpora -- and then fit a task-specific classifier on top.… 37 arXiv — NLP / Computation & Language research 1mo ago Comprehensive Evaluation of Large Language Model Responses: A Multi-Factor Scoring System arXiv:2607.06940v1 Announce Type: new Abstract: The remarkable performance of large language models (LLMs) in linguistic tasks underscores an urgent need for comprehensive evaluation of their response quality. Prevailing methods, often confined to singular dimensions, fall short… 26 arXiv — NLP / Computation & Language research 1mo ago Evaluation of Multilingual Ability to Use Spatial Deictic Expressions in Vision-Language Models arXiv:2607.07251v1 Announce Type: new Abstract: One of the expected abilities of vision-language models (VLMs) is spatial reasoning ability based on a given text and image. To evaluate the spatial reasoning abilities of VLMs, we focus on the use of spatial deictic expressions,… 5 arXiv — NLP / Computation & Language research 1mo ago Simulstream: Open-Source Toolkit for Evaluation and Demonstration of Streaming Speech-to-Text Translation Systems arXiv:2512.17648v2 Announce Type: replace Abstract: Streaming Speech-to-Text Translation (StreamST) requires producing translations concurrently with incoming speech under strict latency constraints, demanding models that balance low latency with high translation quality.… 7 arXiv — NLP / Computation & Language research 1mo ago Practicing with Language Models Cultivates Human Empathic Communication arXiv:2603.15245v2 Announce Type: replace Abstract: Empathy is central to human connection, yet people often struggle to express it effectively. In blinded evaluations, large language models (LLMs) generate responses that are often judged more empathic than human-written ones.… 25 Hugging Face Daily Papers research 1mo ago RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies Abstract RoboDojo presents a unified sim-and-real benchmark for evaluating generalist robot manipulation policies across diverse tasks and evaluation dimensions. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Generalist robot manipulation policies have advanced rapidly, yet… 32 r/LocalLLaMA community 1mo ago Which open models help the eco system more? https://artificialanalysis.ai/evaluations/artificial-analysis-openness-index In case you want to support openness, some models are more open than others. Update: K2 think v2 is rated highest because it supplies its training data and training regimen. This allows anyone with… 25 TechCrunch — AI news-outlet 1mo ago Lovable reportedly in talks to double its valuation to $13.2B The $300 million round is expected to be led by Menlo Ventures, Sifted reported. 7 Hugging Face Daily Papers research 1mo ago VIBE: Voice-Induced open-ended Bias Evaluation for Large Audio-Language Models via Real-World Speech Abstract Large Audio-Language Models exhibit systematic generative biases in realistic scenarios when evaluated through open-ended tasks using human-recorded speech, with bias magnitude varying significantly by task and triggered by gender and accent cues. Generated by… 21 TechCrunch — AI news-outlet 1mo ago Prime Intellect raises $130M Series A to help enterprises build their own AI agents Founded in 2024, Prime Intellect’s goal is to give organizations capabilities to train their own agentic systems without relying on frontier AI labs. 11 OpenAI official-blog 1mo ago Separating signal from noise in coding evaluations A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models. 10 Hugging Face Daily Papers research 1mo ago PluraMath: Extending Mathematical Reasoning Evaluation Beyond High-Resource Languages Abstract PluraMath extends the PolyMath dataset to 18 underrepresented languages, revealing persistent gaps in multilingual mathematical reasoning performance between high-resource and low-resource languages. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Mathematical reasoning… 25 TechCrunch — AI news-outlet 1mo ago AI chip maker SambaNova raises $1B at $11B valuation, 5 months after last mega round AI chip maker SambaNova has raised at an $11B valuation months after Intel was rumored to be trying to buy it for about $1.6 billion. 15 arXiv — Machine Learning research 1mo ago Strategic Bargaining in Multi-Buyer Markets: Reinforcement Learning from Verifiable Rewards for LLM Negotiations arXiv:2607.05863v1 Announce Type: new Abstract: Negotiation is a fundamental strategic interaction in management science, characterized by agents attempting to reach agreements while protecting private information, such as reservation costs and hidden valuations. A prevalent yet… 36 arXiv — Machine Learning research 1mo ago Modeling Normal Is All You Need: Joint Latent Clustering for Anomaly Detection in Multimodal Cyber-Physical Systems arXiv:2607.06094v1 Announce Type: new Abstract: Faults on a cyber-physical system (CPS) are too rare and unrepresentative to characterise, or even to select a model on, so detection must instead model normal behaviour; the standard point-adjusted evaluation, however, rewards… 26 arXiv — Machine Learning research 1mo ago x-Prediction Is All You Need:Training-Free Accelerated Generation via Endpoint Decodability arXiv:2607.06114v1 Announce Type: new Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (NFEs). This remains a practical challenge for released checkpoints, since many… 22 arXiv — Machine Learning research 1mo ago A Task-Driven Evaluation of UAV Detection and Tracking under Synthetic Fog arXiv:2607.05467v1 Announce Type: cross Abstract: Fog severely degrades the visibility of small unmanned aerial vehicles (UAVs) in skydominant, long-range imagery, reducing the reliability of downstream detection and tracking. This paper presents a task-driven evaluation… 20 arXiv — Machine Learning research 1mo ago Association Restoration Test: Revealing Restorable Shortcuts after Unlearning arXiv:2607.05726v1 Announce Type: cross Abstract: Association unlearning aims to disable learned label-attribute shortcuts while preserving task performance. Existing evaluations mainly measure output-level robustness or probe whether shortcut attributes remain readable in… 30 arXiv — NLP / Computation & Language research 1mo ago Prompt Robustness Is Task-Dependent: Comparing Objective and Belief-Style Questions in LLM Evaluation arXiv:2607.05554v1 Announce Type: new Abstract: Survey-style evaluations of large language models often treat a prompted response as a measure of a model's values or beliefs. This assumption is particularly fragile when responses are read as evidence of political values, social… 33 Page 10 of 10 · 500 articles ← Newer
