Search: “reasoning”

[AINews] Anthropic Claude Opus 4.7 - literally one step better than 4.6 in every dimension

model-releaseslatent-space

This article from Latent Space discusses Anthropic's Claude Opus 4.7 release, highlighting incremental improvements across multiple performance dimensions compared to the previous 4.6 version. The pie

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An Underexplored Frontier: Large Language Models for Rare Disease Patient Education and Communication -- A scoping review

DGX agent

arXiv:2604.14179v1 Announce Type: new Abstract: Rare diseases affect over 300 million people worldwide and are characterized by complex care pathways, limited clinical expertise, and substantial unmet

applicationsarxiv-cs-cl

17 Apr 2026

Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models

arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow

Local Ai

Beyond Augmentation: Cross-Modal Transformer Fusion with Bi-directional Attention for Low-Data Aneurysm Screening

arXiv:2512.22185v2 Announce Type: replace Abstract: Intracranial aneurysm rupture causes subarachnoid hemorrhage with mortality near 50%, making early detection critical. Although CTA enables rapid sc

local-aiarxiv-cs-cv

Building Trust in the Skies: A Knowledge-Grounded LLM-based Framework for Aviation Safety

arXiv:2604.13101v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into aviation safety decision-making represents a significant technological advancement, yet their sta

safetyarxiv-cs-ai

Calibrate-Then-Delegate: Safety Monitoring with Risk and Budget Guarantees via Model Cascades

arXiv:2604.14251v1 Announce Type: new Abstract: Monitoring LLM safety at scale requires balancing cost and accuracy: a cheap latent-space probe can screen every input, but hard cases should be escalat

safetyarxiv-cs-lg

ChatSVA: Bridging SVA Generation for Hardware Verification via Task-Specific LLMs

model-releasesarxiv-cs-ai

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

Context Over Content: Exposing Evaluation Faking in Automated Judges

arXiv:2604.15224v1 Announce Type: cross Abstract: The extit{LLM-as-a-judge} paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: th

safetyarxiv-cs-cl

Contextuality from Single-State Ontological Models: An Information-Theoretic Obstruction

arXiv:2602.16716v3 Announce Type: replace Abstract: Contextuality is a central feature of quantum theory, traditionally understood as the impossibility of reproducing quantum measurement statistics us

researcharxiv-cs-ai

Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm

model-releasesarxiv-cs-ai

arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed 'Vibe Coding') exposes a critical Context-Fidelity Trade-off: vague user intents ove

Agents

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre

agentsarxiv-cs-ai

Tutorials

Differentiable Object Pose Connectivity Metrics for Regrasp Sequence Optimization

arXiv:2604.14733v1 Announce Type: new Abstract: Regrasp planning is often required when one pick-and-place cannot transfer an object from an initial pose to a goal pose while maintaining grasp feasibi

tutorialsarxiv-cs-ro

Local Ai

DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA

arXiv:2511.22521v2 Announce Type: replace Abstract: Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex doc

local-aiarxiv-cs-cv

Don't Retrieve, Navigate: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG

arXiv:2604.14572v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds LLM responses in external evidence but treats the model as a passive consumer of search results: it never

Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories

arXiv:2603.25903v2 Announce Type: replace Abstract: Scaling robot learning to long-horizon tasks remains a formidable challenge. While end-to-end policies often lack the structural priors needed for e

safetyarxiv-cs-ro

Agents

Enabling Agents to Communicate Entirely in Latent Space

arXiv:2511.09149v4 Announce Type: replace Abstract: While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling

agentsarxiv-cs-lg

Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization

arXiv:2604.14267v1 Announce Type: new Abstract: Search agents extend Large Language Models (LLMs) beyond static parametric knowledge by enabling access to up-to-date and long-tail information unavaila

safetyarxiv-cs-lg

EuropeMedQA Study Protocol: A Multilingual, Multimodal Medical Examination Dataset for Language Model Evaluation

arXiv:2604.14306v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated high proficiency on English-centric medical examinations, their performance often declines when fac

Fact4ac at the Financial Misinformation Detection Challenge Task: Reference-Free Financial Misinformation Detection via Fine-Tuning and Few-Shot Prompting of Large Language Models

arXiv:2604.14640v1 Announce Type: new Abstract: The proliferation of financial misinformation poses a severe threat to market stability and investor trust, misleading market behavior and creating crit

Fall into a Pit, Gain in a Wit: Cognitive-Guided Harmful Meme Detection via Misjudgment Risk Pattern Retrieval

model-releasesarxiv-cs-lg

arXiv:2510.15946v3 Announce Type: replace Abstract: Internet memes have emerged as a popular multimodal medium, yet they are increasingly weaponized to convey harmful opinions through subtle rhetorica

Feedback Adaptation for Retrieval-Augmented Generation

arXiv:2604.06647v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are typically evaluated under static assumptions, despite being frequently corrected through user or ex

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step

safetyarxiv-cs-ai

From Reactive to Proactive: Assessing the Proactivity of Voice Agents via ProVoice-Bench

arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi

GeoAgentBench: A Dynamic Execution Benchmark for Tool-Augmented Agents in Spatial Analysis

model-releasesarxiv-cs-ai

arXiv:2604.13888v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into Geographic Information Systems (GIS) marks a paradigm shift toward autonomous spatial analysis. How

Geometrically Consistent Multi-View Scene Generation from Freehand Sketches

arXiv:2604.14302v1 Announce Type: new Abstract: We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrical

researcharxiv-cs-cv

Industry

Hello Opus 4.7, you are are thinking way extra high!

Claude Opus 4.7 'thinks more' at higher effort levels, particularly on later turns in agentic settings. Anthropic introduced a new 'xhigh' (extra high) effort level between high and max to give users

industryr-chatgpt

Hierarchical Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa

safetyarxiv-cs-cl

Local Ai

How to Disable Thinking mode of Ollama Models Using Copilot CLI?

A guide on disabling thinking mode in Ollama models using the CLI by running models with the `--think=false` flag or using `/set nothink` followed by a prompt. The post likely discusses how to configu

local-air-ollama

Applications

I'll give Anthropic credit for moving quickly. Opus 4.7 Adaptive Thinking now triggers thinking much more often, including for the tasks it …

applicationsethan-mollick--x

I'll give Anthropic credit for moving quickly. Opus 4.7 Adaptive Thinking now triggers thinking much more often, including for the tasks it failed at yesterday. That also means it is doing a lot more

Inclusive Kitchen Design for Older Adults: Generative AI Visualizations to Support Mild Cognitive Impairment

arXiv:2604.13203v1 Announce Type: cross Abstract: Mild Cognitive Impairment (MCI) affects 15-20% of adults aged 65 and older, often making kitchen navigation and independent living difficult, particul

safetyarxiv-cs-ai

Join us at PyCon US 2026 in Long Beach - we have new AI and security tracks this year

model-releasessimon-willison

This year's PyCon US is coming up next month from May 13th to May 19th, with the core conference talks from Friday 15th to Sunday 17th and tutorial and sprint days either side. It's in Long Beach, Cal

Just Pass Twice: Efficient Token Classification with LLMs for Zero-Shot NER

arXiv:2604.05158v2 Announce Type: replace Abstract: Large language models encode extensive world knowledge valuable for zero-shot named entity recognition. However, their causal attention mechanism, w

Label-efficient underwater species classification with logistic regression on frozen foundation model embeddings

arXiv:2604.00313v2 Announce Type: replace Abstract: Automated species classification from underwater imagery is bottlenecked by the cost of expert annotation, and supervised models trained on one data

Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality

arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode

safetyarxiv-cs-cl

Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabi…

model-releasesemad-mostaque--x

Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabilities they couldn't release it. The announcement featured A

Leveraging graph neural networks and mobility data for COVID-19 forecasting

arXiv:2501.11711v2 Announce Type: replace Abstract: The COVID-19 pandemic has claimed millions of lives, spurring the development of diverse forecasting models. In this context, the true utility of co

researcharxiv-cs-lg

Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips

arXiv:2502.07408v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) can be catastrophically disrupted by flipping only a handful of parameter bits. We introduce Deep Neural Lesion (D

MEME-Fusion@CHiPSAL 2026: Multimodal Ablation Study of Hate Detection and Sentiment Analysis on Nepali Memes

arXiv:2604.14218v1 Announce Type: new Abstract: Hate speech detection in Devanagari-scripted social media memes presents compounded challenges: multimodal content structure, script-specific linguistic

Multi-Modal Manipulation via Multi-Modal Policy Consensus

arXiv:2509.23468v3 Announce Type: replace-cross Abstract: Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation

safetyarxiv-cs-lg

PolyBench: Benchmarking LLM Forecasting and Trading Capabilities on Live Prediction Market Data

model-releasesarxiv-cs-lg

arXiv:2604.14199v1 Announce Type: cross Abstract: Predicting real-world events from live market signals demands systems that fuse qualitative news with quantitative order-book dynamics under strict te

PortraitCraft: A Benchmark for Portrait Composition Understanding and Generation

arXiv:2604.03611v2 Announce Type: replace Abstract: Portrait composition plays a central role in portrait aesthetics and visual communication, yet existing datasets and benchmarks mainly focus on coar

Prism: Symbolic Superoptimization of Tensor Programs

model-releasesarxiv-cs-lg

arXiv:2604.15272v1 Announce Type: cross Abstract: This paper presents Prism, the first symbolic superoptimizer for tensor programs. The key idea is sGraph, a symbolic, hierarchical representation that

RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding

arXiv:2604.14885v1 Announce Type: new Abstract: Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigate

Schema Key Wording as an Instruction Channel in Structured Generation under Constrained Decoding

arXiv:2604.14862v1 Announce Type: new Abstract: Constrained decoding has been widely adopted for structured generation with large language models (LLMs), ensuring that outputs satisfy predefined forma

Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local …

model-releasesclem-delangue--x

Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local agents are today: # Start llama.cpp server: llama-server -hf

Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation

arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a

TennisTV: Do Multimodal Large Language Models Understand Tennis Rallies?

arXiv:2509.15602v5 Announce Type: replace Abstract: Multimodal large language models (MLLMs) excel at general video understanding but struggle with fast, high-frequency sports like tennis, where rally

Agents

To go deeper on our new Life Sciences model series, research lead @joyjiao12 and product lead Yunyun Wang joined @AndrewMayne on the OpenAI …

To go deeper on our new Life Sciences model series, research lead @joyjiao12 and product lead Yunyun Wang joined @AndrewMayne on the OpenAI Podcast to discuss how we’re building models for biology, dr

agentsopenai--x