Search: “context”

ScheMatiQ: From Research Question to Structured Data through Interactive Schema Discovery

arXiv:2604.09237v1 Announce Type: new Abstract: Many disciplines pose natural-language research questions over large document collections whose answers typically require structured evidence, tradition

applicationsarxiv-cs-cl

Human

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Research

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

DGX agent

arXiv:2601.22160v2 Announce Type: replace-cross Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies

researcharxiv-cs-ai

13 Apr 2026

See, Hear, and Understand: Benchmarking Audiovisual Human Speech Understanding in Multimodal Large Language Models

arXiv:2512.02231v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely a

SPASM: Stable Persona-driven Agent Simulation for Multi-turn Dialogue Generation

arXiv:2604.09212v1 Announce Type: new Abstract: Large language models are increasingly deployed in multi-turn settings such as tutoring, support, and counseling, where reliability depends on preservin

Syntheses

Synthesis: Harrison-Chase--X

synthesisharrison-chase--xauto-generated

Auto-generated synthesis of 194 entries about harrison-chase--x

'Take Me Home, Wi-Fi Drone': A Drone-based Wireless System for Wilderness Search and Rescue

arXiv:2604.09115v1 Announce Type: cross Abstract: Wilderness Search and Rescue (WiSAR) represents a longstanding and critical societal challenge, demanding innovative and automatic technological solut

agentsarxiv-cs-ro

Local Ai

Tango: Taming Visual Signals for Efficient Video Large Language Models

arXiv:2604.09547v1 Announce Type: new Abstract: Token pruning has emerged as a mainstream approach for developing efficient Video Large Language Models (Video LLMs). This work revisits and advances th

local-aiarxiv-cs-cv

Temporal Dropout Risk in Learning Analytics: A Harmonized Survival Benchmark Across Dynamic and Early-Window Representations

arXiv:2604.08870v1 Announce Type: cross Abstract: Student dropout is a persistent concern in Learning Analytics, yet comparative studies frequently evaluate predictive models under heterogeneous proto

Hardware

TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training

arXiv:2604.09107v1 Announce Type: cross Abstract: Modern LLM reinforcement learning (RL) workloads require a highly efficient weight transfer system to scale training across heterogeneous computationa

hardwarearxiv-cs-ai

The model is not the agent. The harness is. You need to read this recent study, and a blog post from @hwchase17 ... (links below). It will r…

model-releasesharrison-chase--x

The model is not the agent. The harness is. You need to read this recent study, and a blog post from @hwchase17 ... (links below). It will resonate deeply. This diagram from a recent paper captures so

Hardware

TurboOCR: 270–1200 img/s OCR with Paddle + TensorRT (C++/CUDA, FP16) [P]

hardwarer-machinelearning

TurboOCR is a high-performance OCR project that combines PaddleOCR with NVIDIA TensorRT, implemented in C++ and CUDA, achieving throughput of 270–1,200 images per second using FP16 half-precision infe

V-CAGE: Vision-Closed-Loop Agentic Generation Engine for Robotic Manipulation

arXiv:2604.09036v1 Announce Type: new Abstract: Scaling Vision-Language-Action (VLA) models requires massive datasets that are both semantically coherent and physically feasible. However, existing sce

agentsarxiv-cs-ro

WAND: Windowed Attention and Knowledge Distillation for Efficient Autoregressive Text-to-Speech Models

arXiv:2604.08558v1 Announce Type: cross Abstract: Recent decoder-only autoregressive text-to-speech (AR-TTS) models produce high-fidelity speech, but their memory and compute costs scale quadratically

researcharxiv-cs-ai

Which Pieces Does Unigram Tokenization Really Need?

arXiv:2512.12641v2 Announce Type: replace Abstract: The Unigram tokenization algorithm offers a probabilistic alternative to the greedy heuristics of Byte-Pair Encoding. Despite its theoretical elegan

if you don't own your harness, you don't own your memory this is so true. even though Codex is an open source, it generates an encrypted com…

model-releasesharrison-chase--x

if you don't own your harness, you don't own your memory this is so true. even though Codex is an open source, it generates an encrypted compaction summary (that is not usable outside of the OpenAI ec

12 Apr 2026

Local Ai

model page: https://ollama.com/library/minimax-m2.7

MiniMax-M1 is a large-scale open-weight reasoning model developed by MiniMax, featuring a hybrid Mixture-of-Experts (MoE) architecture with 456 billion total parameters (activating 45.9 billion per to

local-aiollama--x

12 Apr 2026

This one gives a lot of perspective over the fact that memory isn't just a plugin anymore. My take is, each approach has it's tradeoffs but …

This one gives a lot of perspective over the fact that memory isn't just a plugin anymore. My take is, each approach has it's tradeoffs but for me the mental model is, if the memory is more than or 80

12 Apr 2026

Memory + harness, or as @matt_slotnick put it, memory + intent. Something I describe a lot about @usebrief, that why you remember somethin…

Memory + harness, or as @matt_slotnick put it, memory + intent. Something I describe a lot about @usebrief, that *why* you remember something is more important than pure recall. A moment that’s trivia

11 Apr 2026

Relying on model providers' stateful APIs or harnesses creates lock-in: switching models means losing your agent's memory -- a cost that onl…

Relying on model providers' stateful APIs or harnesses creates lock-in: switching models means losing your agent's memory -- a cost that only grows as agents get better at learning a big part of agent

11 Apr 2026

What if owning the memory layer goes far beyond escaping lock-in? What if memory becomes fully editable intelligence? You could debug bad pa…

What if owning the memory layer goes far beyond escaping lock-in? What if memory becomes fully editable intelligence? You could debug bad patterns, reinforce good ones, and crucially synthesize new on

11 Apr 2026

Safety

A systematic framework for generating novel experimental hypotheses from language models

arXiv:2408.05086v3 Announce Type: replace Abstract: Neural language models (LMs) have been shown to capture complex linguistic patterns, yet their utility in understanding human language and more broa

safetyarxiv-cs-cl

Accelerating data curation with Google Data Cloud

model-releasesgoogle-cloud-ai

In the enterprise landscape, data is often highly fragmented across multiple source systems. Data curation is the process of organizing, cleaning, and enriching raw data to transform it into high-qual

Action Without Interaction: Probing the Physical Foundations of Video LMMs via Contact-Release Detection

model-releasesarxiv-cs-cv

arXiv:2511.20162v2 Announce Type: replace Abstract: Large multi-modal models (LMMs) show increasing performance in realistic visual tasks for images and, more recently, for videos. For example, given

Adversarial Evasion Attacks on Computer Vision using SHAP Values

arXiv:2601.10587v2 Announce Type: replace Abstract: The paper introduces a white-box attack on computer vision models using SHAP values. It demonstrates how adversarial evasion attacks can compromise

researcharxiv-cs-cv

AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models

arXiv:2405.16240v3 Announce Type: replace Abstract: In this paper, we introduce analytic federated learning (AFL), a new training paradigm that brings analytical (i.e., closed-form) solutions to the f

researcharxiv-cs-lg

Agent skills are great. I wanted to share some of my favorites from Jesse Vincent's 'Superpowers' skill pack 𝚠𝚛𝚒𝚝𝚒𝚗𝚐-𝚙𝚕𝚊𝚗𝚜 skill…

model-releasesharrison-chase--x

Agent skills are great. I wanted to share some of my favorites from Jesse Vincent's 'Superpowers' skill pack 𝚠𝚛𝚒𝚝𝚒𝚗𝚐-𝚙𝚕𝚊𝚗𝚜 skill produces much better plans than any harness' built in plan mode that I'

Agree! Such sub agents are going to be big

The specific tweet (status ID 2042726390617764234) could not be retrieved directly, as it does not appear in available search results and X/Twitter requires authentication to access individual post...

AI generates well-liked but templatic empathic responses

arXiv:2604.08479v1 Announce Type: new Abstract: Recent research shows that greater numbers of people are turning to Large Language Models (LLMs) for emotional support, and that people rate LLM respons

applicationsarxiv-cs-cl

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s

AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage

arXiv:2505.20662v3 Announce Type: replace Abstract: Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods oft

Before We Trust Them: Decision-Making Failures in Navigation of Foundation Models

arXiv:2601.05529v5 Announce Type: replace Abstract: High success rates on navigation-related tasks do not necessarily translate into reliable decision making by foundation models. To examine this gap,

Tutorials

Brainstorming with ChatGPT

The OpenAI Academy 'Brainstorming with ChatGPT' tutorial is part of OpenAI Academy's library of tutorials and resources designed to help users leverage ChatGPT for idea generation and creative prob...

tutorialsopenai

Hardware

CodecSight: Leveraging Video Codec Signals for Efficient Streaming VLM Inference

arXiv:2604.06036v3 Announce Type: replace-cross Abstract: Video streaming analytics is a crucial workload for vision-language model serving, but the high cost of multimodal inference limits scalabilit

hardwarearxiv-cs-cv

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs

arXiv:2510.12184v2 Announce Type: replace Abstract: Recently, efficient Multimodal Large Language Models (MLLMs) have gained significant attention as a solution to their high computational complexity,

applicationsarxiv-cs-cv

CubeGraph: Efficient Retrieval-Augmented Generation for Spatial and Temporal Data

arXiv:2604.06616v1 Announce Type: cross Abstract: Hybrid queries combining high-dimensional vector similarity search with spatio-temporal filters are increasingly critical for modern retrieval-augment

applicationsarxiv-cs-ai

Local Ai

Data Selection for Multi-turn Dialogue Instruction Tuning

arXiv:2604.07892v1 Announce Type: new Abstract: Instruction-tuned language models increasingly rely on large multi-turn dialogue corpora, but these datasets are often noisy and structurally inconsiste

local-aiarxiv-cs-cl

DBMF: A Dual-Branch Multimodal Framework for Out-of-Distribution Detection

arXiv:2604.08261v1 Announce Type: new Abstract: The complex and dynamic real-world clinical environment demands reliable deep learning (DL) systems. Out-of-distribution (OOD) detection plays a critica

applicationsarxiv-cs-cv

DHFP-PE: Dual-Precision Hybrid Floating Point Processing Element for AI Acceleration

arXiv:2604.04507v2 Announce Type: replace-cross Abstract: The rapid adoption of low-precision arithmetic in artificial intelligence and edge computing has created a strong demand for energy-efficient

researcharxiv-cs-ro

Direct Segmentation without Logits Optimization for Training-Free Open-Vocabulary Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.07723v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment arbitrary category regions in images using open-vocabulary prompts, necessitating that exis

Distributed Multi-Layer Editing for Rule-Level Knowledge in Large Language Models

arXiv:2604.08284v1 Announce Type: new Abstract: Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, an

Safety

Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook

arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac

safetyarxiv-cs-ai

Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing

arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th

Efficient Quantization of Mixture-of-Experts with Theoretical Generalization Guarantees

arXiv:2604.06515v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) allows scaling of language and vision models efficiently by activating only a small subset of experts per input. While

researcharxiv-cs-ai

Emotion Concepts and their Function in a Large Language Model

arXiv:2604.07729v1 Announce Type: cross Abstract: Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore imp

Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models

arXiv:2604.08456v1 Announce Type: cross Abstract: Despite rapid progress, pretrained vision-language models still struggle when answers depend on tiny visual details or on combining clues spread acros

researcharxiv-cs-cl

EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

arXiv:2603.11703v2 Announce Type: replace Abstract: We introduce EvoFlows, a variable-length protein sequence-to-sequence modeling approach designed for protein engineering. Existing protein language

researcharxiv-cs-lg

Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning

arXiv:2603.02070v2 Announce Type: replace-cross Abstract: When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facil

agentsarxiv-cs-cl

FBS: Modeling Native Parallel Reading inside a Transformer

arXiv:2601.21708v2 Announce Type: replace Abstract: Large language models (LLMs) excel across many tasks, yet inference is still dominated by strictly token-by-token autoregression. Existing accelerat

researcharxiv-cs-ai