Search: “evaluation”

Making Alternative Data Work: Context-Augmented LLMs for Financial Forecasting

arXiv:2609.11607v1 Announce Type: new Abstract: When forecasting a firm's future financial performance, alternative data - data collected from non-traditional sources such as consumer transactions, we

Industry

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DGX agent

More in depth thoughts Thoughts on @DarioAmodei's pacing the frontier proposal. I think its well intentioned but has logical flaws, as does our implicit belief intelligence is a crime. Even OpenAI's b

industryemad-mostaque--x

12 Sept 2026

MOSAIC: Query-Aware Exploration Policy Adaptation for GraphRAG

arXiv:2609.11065v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) can connect evidence distributed across a corpus graph, but most systems use largely shared exploration

Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation

arXiv:2607.18029v2 Announce Type: replace-cross Abstract: Researchers need to answer ad-hoc questions about the contents of domain-specific archives but often lack the expertise to write structured qu

agentsarxiv-cs-ai

Off-Target Effects of Response-Style Alignment in a Korean 27B Language Model

arXiv:2609.11291v1 Announce Type: new Abstract: We post-train Qwen3.8-27B for Korean response style -- verbosity, list and markdown usage, discourse structure and register -- and measure two behaviour

Spectral Masking and Interpolation Attack (SMIA): A Black-box Adversarial Attack against Voice Authentication and Anti-Spoofing Systems

arXiv:2509.07677v5 Announce Type: replace-cross Abstract: Voice Authentication Systems (VAS) use unique vocal characteristics for verification. They are increasingly integrated into high-security sect

applicationsarxiv-cs-ai

THE CURE IS THE PITCH Dario’s 'Pacing' Essay Is Quiet-Period Illegal Stock Promotion Wrapped in Regulatory Capture Dario Amodei's 'We Must P…

model-releasesyann-lecun--x

THE CURE IS THE PITCH Dario’s 'Pacing' Essay Is Quiet-Period Illegal Stock Promotion Wrapped in Regulatory Capture Dario Amodei's 'We Must Pace the Frontier' is not a safety paper. It is a pre-roadsho

Industry

This is the most interesting part of this proposal I think. We can be very specific here - data is the most important ingredient. Do not tra…

This is the most interesting part of this proposal I think. We can be very specific here - data is the most important ingredient. Do not train general purpose models on cyber attack or any biological

industryemad-mostaque--x

Industry

Thoughts on @DarioAmodei's pacing the frontier proposal. I think its well intentioned but has logical flaws, as does our implicit belief int…

Thoughts on @DarioAmodei's pacing the frontier proposal. I think its well intentioned but has logical flaws, as does our implicit belief intelligence is a crime. Even OpenAI's board weren't powerful e

industryemad-mostaque--x

Timely Clinical Diagnosis through Active Test Selection

arXiv:2510.18988v5 Announce Type: replace Abstract: There is growing interest in using machine learning (ML) to support clinical diagnosis, but most approaches rely on static, fully observed datasets

applicationsarxiv-cs-ai

Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations

arXiv:2609.11805v1 Announce Type: cross Abstract: Maritime Autonomous Surface Ships (MASS) and AI- supported decision assistants are expected to transform maritime operations, but their safe integrati

agentsarxiv-cs-ai

Safety

“We can’t slow down because China will beat us.” We can slow down. Chinese AI is waterskiing behind the US. Their AI capabilities come at a …

“We can’t slow down because China will beat us.” We can slow down. Chinese AI is waterskiing behind the US. Their AI capabilities come at a delay since they mainly come from distilling US AIs. If we s

safetydan-hendrycks--x

X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation

arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular

researcharxiv-cs-ai

3D Point Splatting for mmWave Radar Novel View Synthesis

arXiv:2609.11894v1 Announce Type: new Abstract: Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoi

researcharxiv-cs-cv

A Dynamic Toolkit for Transmission Characteristics of Precision Reducers with Explicit Contact Geometry

arXiv:2604.02387v3 Announce Type: replace Abstract: Precision reducers couple contact geometry, bearing support, structural deformation, and loading history. This paper presents a dynamic toolkit conn

local-aiarxiv-cs-ro

A Group-Based Resource Allocation Model for the Fractional Knapsack Problem

arXiv:2609.06470v2 Announce Type: replace-cross Abstract: To solve the fractional knapsack problem, Dantzig's greedy rule orders items according to their value-to-cost ratio. This ordering introduces

researcharxiv-cs-cl

A Multi-Stage Rule-Chaining Framework for Compositional and Interpretable Cognitive Reasoning

arXiv:2609.10654v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) benchmarks cognitive generalization, the ability to infer and apply abstract rules from limited examples. T

researcharxiv-cs-lg

AcFlow: Controlling Text-to-Image Diffusion Transformers via Learned Conditional Activation Flow

arXiv:2609.10723v1 Announce Type: new Abstract: Text-to-image diffusion transformers (DiTs) are powerful generators, yet direct prompting provides limited control interface for style intensity and can

Active noise cancellation on open-ear smart glasses

arXiv:2604.05519v2 Announce Type: replace-cross Abstract: Active noise cancellation (ANC) is widely deployed on consumer headphones and earbuds to suppress environmental noise. However, existing ANC s

researcharxiv-cs-lg

AdamX: Cosine similarity meets gradient descent

arXiv:2609.11867v1 Announce Type: new Abstract: We introduce AdamX, a first-order optimizer that incorporates cosine similarity as an adaptive mechanism for controlling update magnitudes. The proposed

Safety

Adaptive Diffusion Freezing: Privacy-preserving Diffusion Models Against Membership Inference Attacks

arXiv:2609.10608v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in generative tasks across various areas, however their training process raises significant privacy

safetyarxiv-cs-lg

Addressing A Posteriori Performance Degradation in Neural Network Subgrid Stress Models

arXiv:2511.17475v2 Announce Type: replace-cross Abstract: Neural network subgrid stress models often have a priori performance that is far better than the a posteriori performance, leading to neural n

researcharxiv-cs-lg

Aerodynamic Prior-Free Coordinated Trajectory Generation and Tracking Control for a Tail-Sitter UAV

model-releasesarxiv-cs-ro

arXiv:2609.11698v1 Announce Type: new Abstract: This paper presents a coordinated trajectory generation and tracking control framework for a tail-sitter unmanned aerial vehicle (UAV), which does not r

AI Economist Agent: An Agentic Framework for Evidence-Based Economic and Financial Analysis with RAG, Knowledge Graphs, and Large Language Models

arXiv:2606.20041v2 Announce Type: replace-cross Abstract: We propose an AI economist agent for economic and financial scenario analysis. Scenario design often requires analysts to assess emerging risk

agentsarxiv-cs-lg

Are we missing a benchmark for agent runtimes, not just models?

model-releasesr-localllama

We have SWE-bench, Terminal-Bench, OSWorld, BrowseComp, etc. But I haven’t seen a good apples-to-apples benchmark for platforms like OpenAI Agents, Anthropic’s agent stack, AWS AgentCore, Google’s age

Astra is one of the best models we've tested at parsing complex documents with tables, at 93.2% on ParseBench. So it seems well suited for a…

model-releasesjerry-liu--x

Astra is one of the best models we've tested at parsing complex documents with tables, at 93.2% on ParseBench. So it seems well suited for ad-hoc analysis over table-heavy documents e.g. in finance. T

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

model-releasesarxiv-cs-cl

arXiv:2609.11870v1 Announce Type: new Abstract: A language model normally begins training with random word embeddings: whatever 'banana' means must be learned from training corpora. I implement St. Au

Hardware

Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System

arXiv:2609.10922v1 Announce Type: new Abstract: Auto-research agents have shown the potential to automate hypothesis generation, experiment execution, and iterative refinement. However, scaling this p

hardwarearxiv-cs-cl

BruNet: A Cross-Domain Transfer Framework for Bruise Segmentation

arXiv:2609.11463v1 Announce Type: new Abstract: Segmenting bruises is a challenging task in medical imaging due to limited data and annotations, diffuse boundaries, and highly variable appearance. In

local-aiarxiv-cs-cv

Building Supervision into Hebbian Plasticity through Spike Agreement

arXiv:2601.08526v2 Announce Type: replace-cross Abstract: Supervised learning in spiking neural networks (SNNs) typically requires either gradient-based backpropagation, which sacrifices the Hebbian,

CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation

arXiv:2609.10943v1 Announce Type: new Abstract: The integration of large language models (LLMs) into video generation has enabled rapid text-to-video creation and improved visual quality. However, it

Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

model-releasesarxiv-cs-cl

arXiv:2609.11141v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate structured outputs, but their reliability remains unclear when those outputs must satisfy

CEM-TUDASR: Computationally efficient multi-modality transformer based unsupervised domain adaptive super-resolution approach

arXiv:2609.11201v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) enables non-invasive visualization of the gastrointestinal tract, but its miniaturized optics, sensor limitations, and

local-aiarxiv-cs-cv

CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models

arXiv:2509.22360v2 Announce Type: replace Abstract: Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora

researcharxiv-cs-cl

CMNIE: An Information Extraction Benchmark for Chinese Military News

model-releasesarxiv-cs-cl

arXiv:2609.10722v1 Announce Type: new Abstract: Structured extraction from Chinese military news supports intelligence analysis, decision-making, and knowledge base construction. However, existing res

ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance

arXiv:2609.09458v1 Announce Type: new Abstract: As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks

local-aiarxiv-cs-ai

Decision Shifts, Lost Label Functionality, and an Inconclusive Grounding Audit in Correctness-Gated Multi-Teacher Distillation

arXiv:2609.09702v1 Announce Type: new Abstract: Candidate decision correctness and rationale grounding are different objectives. We examine correctness-gated multi-teacher distillation in a fixed expe

DefVINS: Visual-Inertial Odometry for Deformable Scenes

arXiv:2601.00702v3 Announce Type: replace-cross Abstract: Deformable scenes violate the rigidity assumptions underpinning classical visual--inertial odometry (VIO), often leading to over-fitting to lo

Detecting hallucinations in local models without eating VRAM: What we learned testing 1.5B to 120B models

Hey everyone, If you run local models via Ollama in production or personal projects, you've probably run into the hallucination problem: how do you know when a model is hallucinating without burning e

model-releasesr-ollama

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

arXiv:2609.11777v1 Announce Type: cross Abstract: Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decisio

applicationsarxiv-cs-lg

Divergence-Based Similarity Function for Multi-View Contrastive Learning

arXiv:2507.06560v5 Announce Type: replace Abstract: Recent success in contrastive learning has sparked growing interest in more effectively leveraging multiple augmented views of data. While prior met

researcharxiv-cs-cv

DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents

arXiv:2609.10892v1 Announce Type: cross Abstract: When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls,

EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression

arXiv:2609.11058v1 Announce Type: new Abstract: Recent advances in multimodal large language mod- els (MLLMs) have opened new opportunities for edge intelligence by enabling reasoning across heterogen

Safety

Evidence for Limited Metacognition in LLMs

arXiv:2509.21545v3 Announce Type: replace Abstract: The possibility of LLM self-awareness and even sentience is gaining increasing public attention and has major safety and policy implications, but th

safetyarxiv-cs-lg

Expressive Robotic Pianist: Mastering Complex Piano Repertoire with Graph-Mimic and Musical Dynamics

arXiv:2609.10844v1 Announce Type: new Abstract: Enabling robots to perform musical instruments with human-level expressivity represents a frontier in bridging the gap between mechanical precision and

applicationsarxiv-cs-ro

ExpTest: Loss-Curve Hypothesis Testing for Autonomous Learning-Rate Selection in Deep Neural Networks

arXiv:2411.16975v2 Announce Type: replace Abstract: Hyperparameter tuning remains a significant challenge in the training of deep neural networks (DNNs), requiring manual search or time-intensive grid

agentsarxiv-cs-lg

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

model-releasesarxiv-cs-ro

arXiv:2609.11445v1 Announce Type: new Abstract: Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring

Fast and Accurate Monomodal 3D High Resolution Deep Registration of Drosophila Larval Brain Volumes

arXiv:2609.11240v1 Announce Type: new Abstract: The larval stage of Drosophila melanogaster is a compact model system for neuroscience whose genetic toolkit allows fluorescent markers to be expressed