Search: “context”

For what it's worth. I'm a mechanical engineer by education and software engineer in practice over the past ~20 years. Playing around with local models has been a recent hobby. Today I decided to do a

I need you guys to understand just how insanely good Meta Muse is at idea generation. Look at your “ideas” tab. The AI labs - OpenAI, Anthropic, and Google - were always showing the same three use cas

I ran a small test for Dory to see whether a local model could update one fact in a synthetic notes file without losing any of the others. I asked Gemma and Qwen to rewrite the file, return a patch, o

Nice paper on agent memory. It explores an effective routing mechanism for memory in agents. The overall finding is that you want a separate retrieval strategy for each type of memory instead of one e

Noah Smith (@noahopinion) has become deeply intellectually dishonest. If he actually followed the field he would a. understand the difference between pure LLMs and LLMs with neurosymbolic harnesses, c

arXiv:2610.11716v1 Announce Type: cross Abstract: We describe a 4-tensor attention model that predicts the next semantic state of a scene, for video generation and robot planning. A window of states h

arXiv:2403.18791v4 Announce Type: replace Abstract: Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very l

arXiv:2610.11724v1 Announce Type: new Abstract: Multimodal meme understanding is increasingly used to analyze socially sensitive content, yet existing models often exhibit biased behavior when interpr

arXiv:2610.11060v1 Announce Type: cross Abstract: World-action models have recently improved autonomous driving by jointly learning future scene prediction and trajectory generation. Most existing app

arXiv:2610.10628v1 Announce Type: cross Abstract: Existing LLM-based approaches for software Requirements Engineering (RE) typically rely on basic prompting strategies or rudimentary agent collaborati

arXiv:2610.11613v1 Announce Type: new Abstract: An agent can complete a task without improving how it works. Turning task experience into reusable capability requires connecting the changed component

arXiv:2507.14897v2 Announce Type: replace Abstract: Methods to build LLM agents have evolved from prompt engineering and supervised finetuning to agentic reinforcement learning (agentic RL). However,

arXiv:2610.10770v1 Announce Type: cross Abstract: How might AI alter how we understand and experience the self? This scoping review analyzes 102 papers to examine how the self is defined in the field

arXiv:2610.11896v1 Announce Type: new Abstract: Assembly documentation is a downstream manufacturing artifact that is still usually authored by interpreting CAD models by hand. Structured product data

arXiv:2511.02374v2 Announce Type: replace-cross Abstract: Current large language models excel at broad, general-purpose tasks, but consistently underperform when exposed to highly specialized domains

meta : handle host views (#30217) meta : handle views of tensors allocated on the host A view shares the memory of its view_src, so ggml-alloc never allocates a view in the buffer of the split it land

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement, since so many variables are at play (notes, skills, tool c

arXiv:2610.10875v1 Announce Type: new Abstract: Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the not

arXiv:2610.10663v1 Announce Type: cross Abstract: Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-lang

arXiv:2610.11283v1 Announce Type: cross Abstract: Humanoid loco-manipulation requires coordinated locomotion and manipulation informed by future scene evolution and whole-body motion, yet learning the

arXiv:2610.11305v1 Announce Type: new Abstract: A language model may revise the same proposition after receiving genuinely relevant evidence or after receiving directional user pressure that adds no r

arXiv:2610.10974v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target policy from logged data, but limited behavior-policy coverage can force high-variance rewe

arXiv:2610.11683v1 Announce Type: new Abstract: Fusing a learned camera-noise fingerprint with an RGB appearance backbone is an appealing route to generator-independent deepfake detection, because the

arXiv:2610.12445v1 Announce Type: cross Abstract: Recent incidents have highlighted the challenge of monitoring LLM agents and the danger of models deceiving people. We show that white-box deception d

arXiv:2610.11542v1 Announce Type: cross Abstract: Multi-agent LLM systems negotiating with a stateful counterpart waste model calls in three ways: polite loops that never meet the counterpart's hidden

arXiv:2610.10641v1 Announce Type: cross Abstract: Large language models (LLMs) offer promising potential for next-visit diagnosis prediction, owing to their ability to integrate longitudinal clinical

arXiv:2610.11222v1 Announce Type: cross Abstract: Preclinical models poorly predict human drug efficacy, particularly in neurological disorders. Neural activity offers a uniquely rich source of transl

arXiv:2610.10550v1 Announce Type: new Abstract: Personalizing text-to-image diffusion models from a few reference images requires preserving subject identity while following prompts that describe new

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

arXiv:2610.12355v1 Announce Type: cross Abstract: Spatial reasoning remains a persistent weakness of vision-language models (VLMs), because RGB inputs do not directly provide geometric evidence. Exist

arXiv:2607.16656v2 Announce Type: replace Abstract: Object removal aims to eliminate target objects specified by a mask while preserving visual consistency with the surrounding regions. Existing metho

arXiv:2610.12095v1 Announce Type: new Abstract: Few-shot learning aims to recognize novel categories from limited labeled examples. Recent studies incorporate textual semantics to compensate for limit

arXiv:2610.11790v1 Announce Type: new Abstract: Byte-level language models such as the Byte Latent Transformer (BLT) group bytes into patches and run their large global model once per patch. BLT start

arXiv:2610.11384v1 Announce Type: new Abstract: Reinforcement learning is commonly used to train language agents in interactive environments, but cannot be directly applied when rewards are unavailabl

arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas

arXiv:2610.11665v1 Announce Type: new Abstract: Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neig

arXiv:2610.12427v1 Announce Type: cross Abstract: Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under boun

arXiv:2602.01683v2 Announce Type: replace-cross Abstract: Transitioning Multimodal Large Language Models (MLLMs) from offline to online streaming video understanding is essential for continuous percep

arXiv:2610.11314v1 Announce Type: new Abstract: Large Language Models (LLMs) serving as long-term dialogue agents require memory systems that support reliable reasoning over extended interactions. How

arXiv:2610.12305v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) can describe increasingly complex visual scenes, token-level grounding becomes crucial. Yet, when an MLLM ge

arXiv:2610.11129v1 Announce Type: new Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated G

arXiv:2610.11215v1 Announce Type: new Abstract: Reconstructing complete, scene-aligned 3D objects from casual images requires integrating sparse, uncertain observations and inferring surfaces hidden b

arXiv:2510.00536v2 Announce Type: replace Abstract: Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. How

Building an AI agent that works in a demo is a different problem from running one for 40 million developers. Postman and AWS share the architectural patterns behind Agent Mode: controlling tool sprawl

arXiv:2610.10962v1 Announce Type: cross Abstract: Agentic AI based on Large Language Model generalization capabilities offers a wide range of potential applications, including planning for embodied ta

Interesting paper from Sakana AI on memory for recurrent models. Recurrent models are good at state tracking, but they usually keep everything in one hidden vector, so short-term computation and long-