Search: “retrieval”

One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding

arXiv:2604.14149v1 Announce Type: new Abstract: Long video understanding is inherently challenging for vision-language models (VLMs) because of the extensive number of frames. With each video frame ty

local-aiarxiv-cs-cv

Human

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Research

Person Re-Identification via Generalized Class Prototypes

DGX agent

arXiv:2510.17043v2 Announce Type: replace Abstract: Advanced feature extraction methods have significantly contributed to enhancing the task of person re-identification. In addition, modifications to

researcharxiv-cs-cv

16 Apr 2026

pi-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data

arXiv:2604.14054v1 Announce Type: cross Abstract: Deep search agents have emerged as a promising paradigm for addressing complex information-seeking tasks, but their training remains challenging due t

POINTS-Seeker: Towards Training a Multimodal Agentic Search Model from Scratch

arXiv:2604.14029v1 Announce Type: new Abstract: While Large Multimodal Models (LMMs) demonstrate impressive visual perception, they remain epistemically constrained by their static parametric knowledg

agentsarxiv-cs-cv

RadAgents: Multimodal Agentic Reasoning for Chest X-ray Interpretation with Radiologist-like Workflows

arXiv:2509.20490v4 Announce Type: replace-cross Abstract: Agentic systems offer a potential path to solve complex clinical tasks through collaboration among specialized agents, augmented by tool use a

Hardware

SemiFA: An Agentic Multi-Modal Framework for Autonomous Semiconductor Failure Analysis Report Generation

arXiv:2604.13236v1 Announce Type: new Abstract: Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equipment telemetry, consult historical defect records, a

hardwarearxiv-cs-cv

Applications

SuperGrasp: Single-View Object Grasping via Superquadric Similarity Matching, Evaluation, and Refinement

arXiv:2603.29254v2 Announce Type: replace Abstract: Robotic grasping from single-view observations remains a critical challenge in manipulation. However, existing methods still struggle to generate re

applicationsarxiv-cs-ro

Tools

Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers

This guide covers how to train and fine-tune multimodal embedding and reranker models using the Sentence Transformers library, enabling systems to work with both text and image data simultaneously. It

toolshugging-face

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

researcharxiv-cs-cv

Training-Free Test-Time Contrastive Learning for Large Language Models

arXiv:2604.13552v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong reasoning capabilities, but their performance often degrades under distribution shift. Existing test-tim

Visual Sparse Steering (VS2): Unsupervised Adaptation for Image Classification using Sparsity-Guided Steering Vectors

arXiv:2506.01247v2 Announce Type: replace Abstract: Steering vision foundation models at test time, without updating foundation-model weights or using labeled target data, is a desirable yet challengi

researcharxiv-cs-cv

Tutorials

Why Your Agents Can’t Read Enterprise Documents — and How to Fix It

AI agents struggle to effectively process and extract information from complex enterprise documents due to limitations in context windows, reasoning capabilities, and handling of unstructured data for

tutorialsdatabricks

Adaptive Test-Time Scaling for Zero-Shot Respiratory Audio Classification

arXiv:2604.12647v1 Announce Type: cross Abstract: Automated respiratory audio analysis promises scalable, non-invasive disease screening, yet progress is limited by scarce labeled data and costly expe

researcharxiv-cs-cl

ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods

arXiv:2603.21011v2 Announce Type: replace-cross Abstract: Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational enginee

agentsarxiv-cs-ai

ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception

arXiv:2604.12255v1 Announce Type: cross Abstract: Dynamic facial expression recognition in the wild remains challenging due to data scarcity and long-tail distributions, which hinder models from effec

b8797

local-aillama-cpp-releases

Build b8797 is a sequentially numbered incremental release of llama.cpp, the open-source C/C++ library for local LLM inference maintained by ggml-org on GitHub. As part of llama.cpp's rapid, continuou

b8802

local-aillama-cpp-releases

**b8802** is a numbered incremental build release of [llama.cpp](https://github.com/ggml-org/llama.cpp), an open-source C/C++ framework for running large language model (LLM) inference locally and in

Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score

arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin

Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering

arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely

Building evidence-based knowledge bases from full-text literature for disease-specific biomedical reasoning

arXiv:2603.28325v3 Announce Type: replace-cross Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, pr

CODESTRUCT: Code Agents over Structured Action Spaces

arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin

CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs

arXiv:2601.11047v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations.

researcharxiv-cs-cl

Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature

arXiv:2604.12243v1 Announce Type: cross Abstract: Scientific hypothesis generation requires tracking how knowledge evolves, not just what is currently known. We introduce Continuous Knowledge Metaboli

DecompSR: A dataset for decomposed analyses of compositional multihop spatial reasoning

arXiv:2511.02627v2 Announce Type: replace Abstract: We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse com

DeepTest Tool Competition 2026: Benchmarking an LLM-Based Automotive Assistant

arXiv:2604.12615v1 Announce Type: new Abstract: This report summarizes the results of the first edition of the Large Language Model (LLM) Testing competition, held as part of the DeepTest workshop at

Drawing on Memory: Dual-Trace Encoding Improves Cross-Session Recall in LLM Agents

arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-

EMBER: Autonomous Cognitive Behaviour from Learned Spiking Neural Network Dynamics in a Hybrid LLM Architecture

arXiv:2604.12167v1 Announce Type: new Abstract: We present (Experience-Modulated Biologically-inspired Emergent Reasoning), a hybrid cognitive architecture that reorganises the relationship between la

agentsarxiv-cs-ai

Empirical Evaluation of PDF Parsing and Chunking for Financial Question Answering with RAG

model-releasesarxiv-cs-cl

arXiv:2604.12047v1 Announce Type: new Abstract: PDF files are primarily intended for human reading rather than automated processing. In addition, the heterogeneous content of PDFs, such as text, table

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

safetyarxiv-cs-cl

Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference

arXiv:2604.12168v1 Announce Type: cross Abstract: The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transport

HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models

arXiv:2604.12229v1 Announce Type: new Abstract: Small language models (SLMs) often struggle with complex mathematical reasoning due to limited capacity to maintain long chains of intermediate steps an

local-aiarxiv-cs-ai

Industry

How do you organize hundreds of chats?

A community discussion thread on r/ChatGPT where users share tips and strategies for managing large volumes of ChatGPT conversation history. The thread reflects a common pain point among heavy users —

industryr-chatgpt

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

researcharxiv-cs-lg

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability

arXiv:2510.03174v2 Announce Type: replace-cross Abstract: Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topi

Applications

LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks

arXiv:2604.12096v1 Announce Type: new Abstract: On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training.

applicationsarxiv-cs-ai

Lyra 2.0: Explorable Generative 3D Worlds

arXiv:2604.13036v1 Announce Type: new Abstract: Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, t

researcharxiv-cs-cv

Masked by Consensus: Disentangling Privileged Knowledge in LLM Correctness

arXiv:2604.12373v1 Announce Type: new Abstract: Humans use introspection to evaluate their understanding through private internal states inaccessible to external observers. We investigate whether larg

local-aiarxiv-cs-cl

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization

arXiv:2604.12237v1 Announce Type: cross Abstract: In drug discovery, molecular optimization aims to iteratively refine a lead compound to improve molecular properties while preserving structural simil

Not All Turns Are Equally Hard: Adaptive Thinking Budgets For Efficient Multi-Turn Reasoning

arXiv:2604.05164v2 Announce Type: replace-cross Abstract: As LLM reasoning performance plateau, improving inference-time compute efficiency is crucial to mitigate overthinking and long thinking traces

Public Profile Matters: A Scalable Integrated Approach to Recommend Citations in the Wild

arXiv:2603.17361v2 Announce Type: replace-cross Abstract: Proper citation of relevant literature is essential for contextualising and validating scientific contributions. While current citation recomm

TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning

arXiv:2512.03963v3 Announce Type: replace Abstract: Enhancing the temporal understanding of Multimodal Large Language Models (MLLMs) is essential for advancing long-form video analysis, enabling tasks

local-aiarxiv-cs-cv

Testing Ollama with Genma 4 and internet search turned on, and got the model extremely confused that it got results from the future

A Reddit post from the r/ollama community documents a user's experiment running Google's Gemma 4 model locally via Ollama with web search (internet access) enabled, which resulted in the model becomin

local-air-ollama

Hardware

🆕 The Full Story of Notion AI https://latent.space/p/notion We're so excited to chat with @simonlast and @sarahmsachs about Notion's 'Token…

🆕 The Full Story of Notion AI https://latent.space/p/notion We're so excited to chat with @simonlast and @sarahmsachs about Notion's 'Token Town' - the crack team of AI Engineers and Model Behavior En

hardwareswyx--x

This is awesome

Jerry Liu, co-founder of LlamaIndex, shared a post on X (formerly Twitter) expressing enthusiasm about a notable development, likely related to AI, large language models, or the LlamaIndex ecosystem.

agentsjerry-liu--x

TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment

model-releasesarxiv-cs-cv

arXiv:2604.12012v1 Announce Type: new Abstract: Recent progress in vision-language pretraining has enabled significant improvements to many downstream computer vision applications, such as classificat