Search: “framework”

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

arXiv:2604.22180v1 Announce Type: cross Abstract: Large language model (LLM) based listwise reranking has emerged as the dominant paradigm for achieving state-of-the-art ranking effectiveness in infor

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Model Releases

Rethinking Retrieval-Augmented Generation as a Cooperative Decision-Making Problem

DGX agent

arXiv:2602.18734v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has demonstrated strong effectiveness in knowledge-intensive tasks by grounding language generation in ex

model-releasesarxiv-cs-ai

27 Apr 2026

Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings

arXiv:2604.22662v1 Announce Type: cross Abstract: Shapley values are a cornerstone of explainable AI, yet their proliferation into competing formulations has created a fragmented landscape with little

safetyarxiv-cs-ai

Robust Localization for Autonomous Vehicles in Highway Scenes

arXiv:2604.22040v1 Announce Type: new Abstract: Localization for autonomous vehicles on highways remains under-explored compared to urban roads, and state-of-the-art methods for urban scenes degrade w

agentsarxiv-cs-ro

SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios

arXiv:2604.22162v1 Announce Type: new Abstract: Automated sports analysis demands robust multi-object tracking (MOT), yet segmentation-based methods often struggle with mask errors and ID switches in

researcharxiv-cs-cv

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning

arXiv:2511.14427v3 Announce Type: replace-cross Abstract: Effective contact-rich manipulation requires robots to synergistically leverage vision, force, and proprioception. However, Reinforcement Lear

safetyarxiv-cs-lg

SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning

arXiv:2604.22558v1 Announce Type: cross Abstract: As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to complex navigation. While Reinforcement Learni

agentsarxiv-cs-ai

StateX: Enhancing RNN Recall via Post-training State Expansion

arXiv:2509.22630v3 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs), such as linear attention and state-space models, have gained popularity due to their constant per-token comp

STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation

arXiv:2604.22282v1 Announce Type: new Abstract: Knowledge Graph-based Question Answering (KGQA) plays a pivotal role in complex reasoning tasks but remains constrained by two persistent challenges: th

researcharxiv-cs-cl

Sum-of-Checks: Structured Reasoning for Surgical Safety with Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.22156v1 Announce Type: cross Abstract: Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectomy is essential to prevent bile duct injury, a comp

System-Mediated Attention Imbalances Make Vision-Language Models Say Yes

arXiv:2601.12430v2 Announce Type: replace Abstract: Vision-language model (VLM) hallucination is commonly linked to imbalanced allocation of attention across input modalities: system, image and text.

safetyarxiv-cs-cl

The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

arXiv:2601.12979v3 Announce Type: replace Abstract: The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive

agentsarxiv-cs-cl

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

arXiv:2505.20435v3 Announce Type: replace-cross Abstract: Existing interpretability methods for Large Language Models (LLMs) predominantly capture linear directions or isolated features. This overlook

Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis

model-releasesarxiv-cs-lg

arXiv:2604.22695v1 Announce Type: cross Abstract: Respiratory airflow signals provide critical insight into breathing mechanics, yet conventional analysis methods remain limited in their ability to ch

TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis

arXiv:2604.22225v1 Announce Type: new Abstract: While generative text-to-speech (TTS) models approach human-level quality, monolithic metrics fail to diagnose fine-grained acoustic artifacts or explai

safetyarxiv-cs-cl

UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions

arXiv:2604.22209v1 Announce Type: cross Abstract: Generative audio modeling has largely been fragmented into specialized tasks, text-to-speech (TTS), text-to-music (TTM), and text-to-audio (TTA), each

UR^2: Unify RAG and Reasoning through Reinforcement Learning

arXiv:2508.06165v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong capabilities through two complementary paradigms: Retrieval-Augmented Generation (RAG) for know

Applications

Video Analysis and Generation via a Semantic Progress Function

arXiv:2604.22554v1 Announce Type: new Abstract: Transformations produced by image and video generation models often evolve in a highly non-linear manner: long stretches where the content barely change

applicationsarxiv-cs-cv

When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters

arXiv:2602.21977v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a leading technique for efficiently fine-tuning text-to-image diffusion models, and its widespread adoptio

researcharxiv-cs-cv

When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models

arXiv:2510.21285v4 Announce Type: replace Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harm

safetyarxiv-cs-ai

Here is a very common problem when building complex agents. Long-horizon agents (in particular) fail in two ways: the decision-maker can't d…

Here is a very common problem when building complex agents. Long-horizon agents (in particular) fail in two ways: the decision-maker can't decompose well, or the skill library goes stale. This new res

safetydair-ai--x

Opened a llama.cpp discussion about whether custom GBNF grammars can compose with tool calls in llama-server. Right now tools work alone, gr…

model-releasesclem-delangue--x

Opened a llama.cpp discussion about whether custom GBNF grammars can compose with tool calls in llama-server. Right now tools work alone, grammar works alone, but tools+grammar doesn't. If you use lla

Industry

Our Principles: Democratization, Empowerment, Universal Prosperity, Resilience, and Adaptability https://openai.com/index/our-principles/

OpenAI's core principles emphasize democratizing access to AI technology, empowering individuals and organizations through AI tools, promoting universal prosperity across society, building resilient A

industrysam-altman--x

TRINITY: An Evolved LLM Coordinator https://arxiv.org/abs/2512.04695

TRINITY is a large language model coordinator system that evolves and improves its approach to orchestrating multiple LLMs or reasoning processes. The system likely uses evolutionary or adaptive mecha

researchdavid-ha--x

Tools

inside me there are two wolves

This post likely references the popular internet meme 'there are two wolves inside you,' which is used to humorously describe internal conflict or competing impulses. Given it's from Swyx, a known tec

toolsswyx--x

25 Apr 2026

Tutorials

Model Risk Management in 2026: A Banker’s Guide to the Revised Interagency Guidance

This guide addresses updated regulatory requirements for model risk management in banking institutions, likely covering the 2026 revisions to interagency guidance issued by banking regulators. It prov

tutorialsdatabricks

25 Apr 2026

Tutorials

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit

tutorialsarxiv-cs-ai

A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking

model-releasesarxiv-cs-lg

arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi

A mathematician who shared an office with Claude Shannon at Bell Labs gave one lecture in 1986 that explains why some people win Nobel Prize…

model-releasesyann-lecun--x

A mathematician who shared an office with Claude Shannon at Bell Labs gave one lecture in 1986 that explains why some people win Nobel Prizes and other equally smart people spend their whole lives doi

A Replicable Robotics Awareness Method Using LLM-Enabled Robotics Interaction: Evidence from a Corporate Challenge

arXiv:2604.21377v1 Announce Type: new Abstract: Large language models are increasingly being explored as interfaces between humans and robotic systems, yet there remains limited evidence on how such t

researcharxiv-cs-ro

Tutorials

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

tutorialsarxiv-cs-ai

Adaptive Soft Error Protection for Neural Network Processing

arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met

researcharxiv-cs-lg

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

ADS-POI: Agentic Spatiotemporal State Decomposition for Next Point-of-Interest Recommendation

arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv

AEL: Agent Evolving Learning for Open-Ended Environments

arXiv:2604.21725v1 Announce Type: cross Abstract: LLM agents increasingly operate in open-ended environments spanning hundreds of sequential episodes, yet they remain largely stateless: each task is s

AI for software engineering: from probable to provable

arXiv:2511.23159v2 Announce Type: replace-cross Abstract: Vibe coding, the much-touted use of AI techniques for programming, faces two overwhelming obstacles: the difficulty of specifying goals ('prom

Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers

arXiv:2507.15753v2 Announce Type: replace-cross Abstract: Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending

Anatomy-Aware Text-Visual Fusion with Dual-Perspective Prompts for Fine-Grained Lumbar Spine Segmentation

arXiv:2504.03476v2 Announce Type: replace Abstract: Accurate lumbar spine segmentation is crucial for diagnosing spinal disorders. Existing methods typically use coarse-grained segmentation strategies

researcharxiv-cs-cv

APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds

model-releasesarxiv-cs-cv

arXiv:2505.09971v3 Announce Type: replace Abstract: Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed

BackPlay: Head-Only Look-Back Self-Correction for Diffusion Language Models

arXiv:2601.06428v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) decode multiple tokens in parallel, but aggressive multi-token decoding amplifies cross-token dependency errors and

researcharxiv-cs-lg

Applications

Behavioral Consistency and Transparency Analysis on Large Language Model API Gateways

arXiv:2604.21083v1 Announce Type: cross Abstract: Third-party Large Language Model (LLM) API gateways are rapidly emerging as unified access points to models offered by multiple vendors. However, the

applicationsarxiv-cs-ai

Beyond N-gram: Data-Aware X-GRAM Extraction for Efficient Embedding Parameter Scaling

model-releasesarxiv-cs-cl

arXiv:2604.21724v1 Announce Type: new Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and

Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents

model-releasesarxiv-cs-cl

arXiv:2604.21134v1 Announce Type: new Abstract: Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely

BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

arXiv:2604.21508v1 Announce Type: new Abstract: Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly gr

BiTDiff: Fine-Grained 3D Conducting Motion Generation via BiMamba-Transformer Diffusion

arXiv:2604.04395v2 Announce Type: replace Abstract: 3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual perfo

safetyarxiv-cs-cv

Building my own Agentic Environment from scratch, in Go, for sandbox-per-agent usage

The Reddit post discusses building a custom agentic environment in Go programming language, specifically designed to provide isolated sandbox environments for individual agents. This approach focuses

agentsr-ollama

Applications

C-SHAP for time series: An approach to high-level temporal explanations

arXiv:2504.11159v2 Announce Type: replace Abstract: In high-stakes domains, such as healthcare and industry, the explainability of AI-based decision-making has become crucial. Without insight into mod

applicationsarxiv-cs-ai

CAP: Controllable Alignment Prompting for Unlearning in LLMs

arXiv:2604.21251v1 Announce Type: cross Abstract: Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearni