Knowledge catalogue
arXiv:2502.14644v5 Announce Type: replace Abstract: Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine
arXiv:2511.14774v3 Announce Type: replace-cross Abstract: Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either
llama.cpp built from source + qwen3.5 27b running locally + hermes agent on top + camofox for scraping (tls spoofing) + scweet to scrape x (no api keys) + tailscale to access from other devices bro Me
LLM Knowledge Base → Slides When @karpathy shared his LLM Knowledge Base setup, many were wondering how to generate more visual forms of the wiki. There are many options, but I think @GammaApp is one
arXiv:2604.09604v1 Announce Type: new Abstract: Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language m
arXiv:2604.10557v1 Announce Type: cross Abstract: This paper argues that Large Language Models (LLMs) should incorporate explicit mechanisms for human empathy. As LLMs become increasingly deployed in
This r/ollama thread discusses how to run a local, free alternative to Claude Code for CLI-based AI coding using Ollama. Ollama v0.14.0 and later are compatible with the Anthropic Messages API, making
arXiv:2604.11348v1 Announce Type: new Abstract: Efficient and explainable breast cancer (BC) risk prediction is critical for large-scale population-based screening. Breast MRI provides functional info
arXiv:2601.14706v3 Announce Type: replace Abstract: In this paper, we present LookBench (We use the term 'look' to reflect retrieval that mirrors how people shop -- finding the exact item, a close sub
arXiv:2604.10044v1 Announce Type: new Abstract: Through systematic experiments on long-context generation, we observe a damaging failure mode in which decoding can collapse into persistent repetition
arXiv:2604.11792v1 Announce Type: new Abstract: Despite rapid progress in video generation, existing models are incapable of producing vector animation, a dominant and highly expressive form of multim
arXiv:2604.11207v1 Announce Type: new Abstract: This paper reviews the LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment. This challenge aims to raise a new direction, i.e., how
arXiv:2604.11446v1 Announce Type: cross Abstract: Recently, scaling reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs) has emerged as an effective training paradigm
arXiv:2604.10862v1 Announce Type: new Abstract: The rapid advancement of diffusion-based generative models has made face forgery detection a critical challenge in digital forensics. Current detection
arXiv:2604.10994v1 Announce Type: new Abstract: In 3D reconstruction, the problem of inverse rendering, namely recovering the illumination of the scene and the material properties, is fundamental. Exi
arXiv:2604.10024v1 Announce Type: cross Abstract: Long video summarization presents significant challenges for current multimodal large language models (MLLMs), particularly in maintaining temporal fi
arXiv:2604.01306v2 Announce Type: replace Abstract: Evaluating scientific arguments requires assessing the strict consistency between a claim and its underlying multimodal evidence. However, existing
M2.7 w/ hermes cli is replacing ~75% of my claude code / opus usage now, but we need clarity for using it as a coding agent @ work. We're truly blessed to have the weights of this one, looking forward
arXiv:2511.18373v2 Announce Type: replace Abstract: Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial
arXiv:2604.11188v1 Announce Type: cross Abstract: Synthesizing high-quality mathematical reasoning data without human priors remains a significant challenge. Current approaches typically rely on seed
arXiv:2604.10169v1 Announce Type: new Abstract: Trajectory prediction remains a critical yet challenging component in autonomous driving systems, requiring sophisticated reasoning capabilities while m
arXiv:2512.01512v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved great success in Speech-to-Text Translation (S2TT) tasks. However, current research is constr
arXiv:2604.09552v1 Announce Type: cross Abstract: Engineering rulebooks and technical standards contain multimodal information like dense text, tables, and illustrations that are challenging for retri
arXiv:2603.22816v3 Announce Type: replace-cross Abstract: Language models increasingly show their work by writing step-by-step reasoning before answering. But are these steps genuinely used, or is the
arXiv:2604.11216v1 Announce Type: new Abstract: What values, evidence preferences, and source trust hierarchies do AI systems actually exhibit when facing structured dilemmas? We present the first lar
arXiv:2604.05795v2 Announce Type: replace Abstract: The increasing use of large language models in mental health applications calls for principled evaluation frameworks that assess alignment with psyc
arXiv:2602.21950v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world
arXiv:2604.10242v1 Announce Type: new Abstract: Despite recent advances in MLLM-based medical image segmentation, existing LISA-like methods cannot reliably reject false queries and often produce hall
arXiv:2603.22241v2 Announce Type: replace Abstract: Diffusion Language Models (DLMs) offer attractive advantages over Auto-Regressive (AR) models, such as full-attention parallel decoding and flexible
arXiv:2604.09852v1 Announce Type: new Abstract: Reasoning models think in long, unstructured streams with no mechanism for compressing or organizing their own intermediate state. We introduce MEMENTO:
arXiv:2601.22361v2 Announce Type: replace-cross Abstract: Assessing the veracity of online content has become increasingly critical. Large language models (LLMs) have recently enabled substantial prog
arXiv:2604.11502v1 Announce Type: cross Abstract: Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate th
arXiv:2604.11012v1 Announce Type: new Abstract: The quality of text generated by large language models depends critically on the decoding sampling strategy. While mainstream methods such as Top-k, Top
arXiv:2604.11578v1 Announce Type: cross Abstract: Measurement-based quantum computation (MBQC) is a framework for quantum information processing in which a computational task is carried out through on
Rashi Shrivastava / Forbes: Mintlify, which uses AI to help companies generate software documentation, raised a 45M Series B led by a16z and Salesforce Ventures at a 500M valuation — It's just one of
arXiv:2601.14671v2 Announce Type: replace Abstract: Autoregressive (AR) visual generators model images as sequences of discrete tokens and are trained with a next-token likelihood objective. This stri
arXiv:2604.11589v1 Announce Type: new Abstract: Automatic evaluation using multimodal large language models (MLLMs), commonly referred to as MLLM-as-a-Judge, has been widely used to measure model perf
arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio
arXiv:2604.10755v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have advanced clinical tasks for common conditions, but their performance on rare diseases remains largely unte
arXiv:2604.11259v1 Announce Type: new Abstract: Mobile GUI agents powered by Multimodal Large Language Models (MLLMs) can execute complex tasks on mobile devices. Despite this progress, most existing
arXiv:2604.10603v1 Announce Type: cross Abstract: Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general pub
arXiv:2604.11762v1 Announce Type: new Abstract: Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been dr
Most AI assistants wait for you to ask. But a truly useful agent should notice you need help before you say anything. New research takes a serious shot at building proactive agents that work in real t
arXiv:2604.09744v1 Announce Type: cross Abstract: The AI agent ecosystem has converged on two protocols: the Model Context Protocol (MCP) for tool invocation and Agent-to-Agent (A2A) for single-princi
arXiv:2604.10126v1 Announce Type: cross Abstract: Metamorphic testing (MT) is a widely recognized technique for alleviating the oracle problem in software testing. However, its adoption is hindered by
arXiv:2604.09717v1 Announce Type: new Abstract: Character recognition is the fundamental part of an optical character recognition (OCR) system. Word recognition, sentence transcription, document digit
arXiv:2604.10347v1 Announce Type: new Abstract: Vision foundation models have been shown to be effective at processing satellite imagery into representations fit for downstream tasks, however, creatin
arXiv:2604.11734v1 Announce Type: cross Abstract: Closed-loop cooperative driving requires planners that generate realistic multimodal multi-agent trajectories while improving safety and traffic effic
arXiv:2604.09967v1 Announce Type: cross Abstract: Muon has emerged as a promising optimizer for large-scale foundation model pre-training by exploiting the matrix structure of neural network updates t
arXiv:2512.00336v2 Announce Type: replace Abstract: The rapid advancement of AI-generated multimodal video-audio content has raised significant concerns regarding information security and content auth
arXiv:2604.11274v1 Announce Type: new Abstract: We present mycelium-index, a streaming approximate nearest neighbor (ANN) index for high-dimensional vector spaces, inspired by the adaptive growth patt
arXiv:2604.10151v1 Announce Type: new Abstract: Large language models are increasingly used as writing tools and pedagogical resources in English for Academic Purposes, but it remains unclear whether
arXiv:2604.10057v1 Announce Type: new Abstract: Accurate state estimation for robotic systems evolving on Lie group manifolds, such as legged robots, is a prerequisite for achieving agile control. How
arXiv:2604.09678v1 Announce Type: cross Abstract: As agentic network management gains popularity, there is a critical need for evaluation frameworks that transcend static, one-shot testing. To address
arXiv:2604.10976v1 Announce Type: cross Abstract: Generalized linear mixed-effects models (GLMMs) are widely used to analyze grouped and hierarchical data. In a GLMM, each response is assumed to follo
arXiv:2604.10414v1 Announce Type: new Abstract: Accurate precipitation estimation is critical for flood forecasting, water resource management, and disaster preparedness. Satellite products provide gl
NEW: Added @OpenRouter's new free stealth model, Elephant-Alpha, to Hermes Agent, which you can now access if you run `hermes update`! I also had Hermes come up with an agentic benchmark on the fly to
arXiv:2604.09940v1 Announce Type: new Abstract: Fine-tuning Large Language Models (LLMs) typically involves either full fine-tuning, which updates all model parameters, or Parameter-Efficient Fine-Tun
New research result: we use Claude to make fully autonomous progress on scalable oversight research, as measured by performance gap recovered (PGR). Claude iterates on a number of different techniques
arXiv:2604.11543v1 Announce Type: cross Abstract: Novelty is a core requirement in academic publishing and a central focus of peer review, yet the growing volume of submissions has placed increasing p