Use this view to inspect the underlying evidence corpus. For ranked developments, decision posture and interpretation, use Signals.
Raw feed or Signals?
Raw feed is chronological evidence. Signals ranks and interprets material change.
Research shows specialist agent decomposition outperforms monolithic LLM prompting in complex European listed real estate financial analysis.
Research identifies bidirectional rationalization in LLM recommendation judges, where zero-shot models convincingly justify opposing outcomes.
Research proposes trajectory-adapted uncertainty quantification for LLM agents to track multi-step error propagation across tool calls.
Researchers applied GRPO reinforcement learning to fine-tune an LLM for financial advice, reportedly beating frontier commercial models.
Paper introduces a hybrid neuro-symbolic framework using LLMs for fact extraction and answer set solvers for deterministic rule reasoning.
Researchers proposed a regime-gated mixture-of-experts model to improve five-day equity realized-volatility forecasting stability.
New research applies speculative decoding to autoregressive time series foundation models, reducing inference latency for long-horizon forecasts.
New arXiv research introduces BrowseSafe, a benchmark and analysis framework evaluating indirect prompt injection risks in AI browser agents.
A new diagnostic stress test measures how system prompts and safety constraints degrade LLM performance relative to standard benchmarks.
Researchers detail a billion-scale Graph Neural Network (GNN) deployed within Weixin Pay for real-time credit fraud detection.
Researchers introduce C-Guard, a framework highlighting that reducing LLM over-refusal of benign prompts silently increases jailbreak vulnerabilities.
Researchers introduce Harness-G, a graph-structured framework to resolve retrieval aliasing in multi-turn search-based RL agents.
Researchers propose a method using almost orthogonal features in language models to perform isolated interventions without downstream entanglement.
Research proposes OrderMoE, a method for deploying Mixture-of-Experts (MoE) models on edge devices by leveraging expert functional similarity.
Research introduces a Stochastic Dimension Zeroth-Order Estimator to improve memory and training efficiency for Physics-Informed Neural Networks (PINNs).
Research reformulates Transformer/Attention mechanisms via measure theory and frequency analysis, claiming hallucination is an inevitable structural LLM limitation.
Research introduces Quantum Port-Hamiltonian Neural Networks (Q-pHNNs) to learn classical dynamics using parameterised quantum circuits.
LakeQuest is a new research benchmark for evaluating question answering systems over heterogeneous, weakly structured data lakes.
Research indicates emotional framing in prompts degrades LLM quantitative reasoning, even when numerical content is identical.
Anthropic is in talks to acquire AI startup Decart for approximately $6 billion in its largest acquisition to date.
Microsoft and S&P Global partner to integrate financial market data and analytics into Microsoft 365 Copilot and agentic workflows.
A supply-chain attack on a compromised AI package exfiltrated terabytes of credentials from 2,500 users.
Private equity firms are structuring debt deals collateralized by Nvidia GPUs, betting the hardware retains resale value across multi-year cycles.
The White House is reportedly planning to expand its AI framework to incorporate governance surrounding open-weights models.
Fintech Mercury launched corporate cards specifically for AI agents, offering dedicated payment credentials, spend limits, and audit trails.
ODNI CIO Doug Cossa called for digital identities for AI agents to adapt Zero Trust security frameworks for autonomous systems.
Alibaba released open weights for its 2.4T-parameter Qwen3.8 model, supported on NVIDIA GB300 NVL72 enterprise hardware.
AWS detailed a pattern for tracking Amazon Bedrock costs by IAM principal, team, and project using AWS CUR 2.0, Athena, and CUDOS.
The Monetary Authority of Singapore is asking banks to verify AI agent identity, permissions, and risk limits prior to transaction execution.
U.S. Bank has launched an AI-powered cash forecasting tool designed to help corporate clients predict cash flows and manage liquidity.
© 2026 OneBench: AI Insights. All rights reserved.
Evidence before opinion