Knowledge catalogue
arXiv:2604.15329v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to simulate human responses in behavioral research, yet it remains unclear when LLM-generated data
arXiv:2604.15521v1 Announce Type: new Abstract: Flow matching models have emerged as a powerful framework for realistic image generation by learning to reverse a corruption process that progressively
arXiv:2503.07520v5 Announce Type: replace Abstract: Traditional supervised drone-view geo-localization (DVGL) methods heavily depend on paired training data and encounter difficulties in learning cros
arXiv:2604.15990v1 Announce Type: cross Abstract: This paper traces a conceptual shift from understanding vulnerability as a static, essentialized property of data subjects to examining how it is acti
arXiv:2502.19312v2 Announce Type: replace-cross Abstract: Effective personalization of LLMs is critical for a broad range of user-interfacing applications such as virtual assistants and content curati
arXiv:2604.15495v1 Announce Type: new Abstract: Navigating complex, densely packed environments like retail stores, warehouses, and hospitals poses a significant spatial grounding challenge for humans
This article from SemiAnalysis analyzes the total cost of ownership for GPU clusters, likely covering hardware expenses, infrastructure requirements, power consumption, and operational overhead beyond
arXiv:2505.13792v2 Announce Type: replace-cross Abstract: Recent advances in reasoning-focused Large Language Models (LLMs) have introduced Chain-of-Thought (CoT) traces - intermediate reasoning steps
Kimi has been the most popular model on Fireworks, both out of the box and as a fine-tuning base (including Composer 2) Now Kimi K2.6 is live with huge jumps (10+%) in coding, long-running agents and
arXiv:2604.15529v1 Announce Type: new Abstract: Current large language models reason in isolation. Although it is common to sample multiple reasoning paths in parallel, these trajectories do not inter
arXiv:2604.15726v1 Announce Type: new Abstract: This position paper argues that large language model (LLM) reasoning should be studied as latent-state trajectory formation rather than as faithful surf
arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical
arXiv:2604.15618v1 Announce Type: new Abstract: We investigate Functional Majority Voting (FMV), a method based on functional consensus for code generation with Large Language Models, which identifies
arXiv:2511.10262v3 Announce Type: replace-cross Abstract: Full-Duplex Speech Language Models (FD-SLMs) enable real-time, overlapping conversational interactions, offering a more dynamic user experienc
arXiv:2509.21623v2 Announce Type: replace-cross Abstract: The expanding long-context capabilities of large language models are constrained by a significant memory bottleneck: the key-value (KV) cache
arXiv:2604.03444v3 Announce Type: replace-cross Abstract: Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid m
arXiv:2604.16235v1 Announce Type: new Abstract: This paper presents a systematic benchmark of state-of-the-art multilingual large language models (LLMs) adapted via token pruning - a compression techn
Cloudflare discusses their approach to implementing AI-powered code review systems across large-scale development operations, likely covering how they leverage AI models to automate code quality check
arXiv:2604.15937v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these
arXiv:2604.15804v1 Announce Type: new Abstract: In this work, we present Qwen3.5-Omni, the latest advancement in the Qwen-Omni model family. Representing a significant evolution over its predecessor,
arXiv:2511.03056v2 Announce Type: replace-cross Abstract: Conversational AI is constrained in many real-world settings where only one side of a dialogue can be recorded, such as telemedicine, call cen
arXiv:2603.13091v2 Announce Type: replace Abstract: The growing interest in embodied agents increases the demand for spatiotemporal video understanding, yet existing benchmarks largely emphasize extra
arXiv:2602.07006v2 Announce Type: replace Abstract: Shoe print evidence recovered from crime scenes plays a key role in forensic investigations. By examining shoe prints, investigators can determine d
arXiv:2603.20633v3 Announce Type: replace Abstract: We present Seed1.8, a foundation model aimed at generalized real-world agency: going beyond single-turn prediction to multi-turn interaction, tool u
arXiv:2509.05489v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards has significantly advanced reasoning in large language models (LLMs), but such signals remain coarse,
arXiv:2511.20834v2 Announce Type: replace-cross Abstract: Sparse Convolution (SpC) powers 3D point cloud networks widely used in autonomous driving and augmented/virtual reality. SpC builds a kernel m
arXiv:2604.15664v1 Announce Type: new Abstract: The rise of autonomous AI agents suggests that dynamic benchmark environments with built-in feedback on scientifically grounded tasks are needed to eval
arXiv:2604.16037v1 Announce Type: new Abstract: The widespread adoption of large language models (LLMs) has increased concerns about their robustness. Vulnerabilities in perturbations of tokenisation
arXiv:2604.16070v1 Announce Type: new Abstract: We present TableSeq, an image-only, end-to-end framework for joint table structure recognition, content recognition, and cell localization. The model fo
arXiv:2604.16123v1 Announce Type: new Abstract: Accurate molecular property prediction is central to drug discovery, catalysis, and process design, yet real-world applications are often limited by sma
Swyx praised a team's livestream event for its excellent production quality and engaging content, noting that it attracted hundreds of live viewers on YouTube. The post reflects positive sentiment abo
arXiv:2604.15383v1 Announce Type: cross Abstract: Large audio-language models (LALMs) generalize across speech, sound, and music, but unified decoders can exhibit a temporal smoothing bias: transient
arXiv:2510.22977v2 Announce Type: replace-cross Abstract: Enhancing the reasoning capabilities of Large Language Models (LLMs) is a key strategy for building Agents that 'think then act.' However, rec
arXiv:2604.16116v1 Announce Type: cross Abstract: We extracted the scholarly reasoning systems of two internationally prominent humanities and social science scholars from their published corpora alon
arXiv:2508.16739v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles (UAVs) have become increasingly important in disaster emergency response by facilitating aerial video analysis. Due to the
arXiv:2601.05547v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in multimodal tasks, but remain susceptible to hallucinations, where gener
arXiv:2510.08480v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have demonstrated remarkable potential in bridging visual and textual reasoning, yet their reliance on text
A user reported satisfaction with Gemma 4 Cloud but switched to GLM 5.1 due to API errors, noting that the alternative model consumes significantly more resources. The post likely discusses the perfor
arXiv:2604.16248v1 Announce Type: new Abstract: Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent
b8850 is a release of llama.cpp that includes CUDA refactoring for AMD matrix multiplication acceleration, with fixes for CDNA and RDNA3 GPU architectures . The release provides precompiled binaries a
This post discusses Graph RAG, an approach that uses local LLMs with Ollama to build graph-based knowledge indexes from source documents by deriving entity knowledge graphs and pregenerating community
Automated lint: 43 errors, 9 warnings, 3 info
shut the f up AIE beat TED???? a somber technical talk about security advisories and maintainer burnout beat the happy storytelling lobster on blazer one on the channel with 27 million subscribers???
Nous Research announced integration or collaboration between Hermes (their AI agent framework) and Ollama (a local LLM runtime platform), enabling users to run Hermes agents with locally-hosted langua
NEW paper from Apple. Interesting idea: 'Attention to Mamba'. The paper introduces a two-stage recipe for cross-architecture distillation from Transformers into Mamba. Naive distillation collapses tea
This post likely discusses how to run the Hermes language model using Ollama, an open-source tool for running large language models locally. It probably provides instructions or insights on setting up
Ollama is a local model-serving engine that enables users to run large language models on their own hardware without relying on cloud services. The post appears to highlight Ollama's integration with
arXiv:2601.08831v5 Announce Type: replace Abstract: Video object segmentation methods like SAM2 achieve strong performance through memory-based architectures but struggle under large viewpoint changes
arXiv:2604.14603v1 Announce Type: cross Abstract: The fundamental limit of natural signal compression has traditionally been characterized by classical rate-distortion (RD) theory through the tradeoff
arXiv:2510.01433v2 Announce Type: replace Abstract: Vision-based robot learning often relies on dense image or point-cloud inputs, which are computationally heavy and entangle irrelevant background fe
arXiv:2512.13671v2 Announce Type: replace Abstract: Industrial anomaly detection (IAD) is challenging due to the subtle and highly localized nature of many defects, which single-pass vision--language
b8824 is a llama.cpp release that optimizes HMX matmul operations, including refactoring functions to use size_t for tile counts and improving readability of core matrix multiplication routines. Relea
Release b8833 of llama.cpp includes updates to the ggml-webgpu backend, fixing compiler warnings and refactoring FlashAttention encoding, along with workflow improvements and precision adjustments for
arXiv:2511.21025v2 Announce Type: replace Abstract: Image captions serve as efficient surrogates for visual content in multimodal systems such as retrieval, recommendation, and multi-step agentic infe
arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad
arXiv:2604.14520v1 Announce Type: new Abstract: Omni-modal Large Language Models (Omni-MLLMs) promise a unified integration of diverse sensory streams. However, recent evaluations reveal a critical pe
arXiv:2604.14856v1 Announce Type: new Abstract: Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, di
arXiv:2604.14630v1 Announce Type: new Abstract: Recent advances in unsupervised video object segmentation have highlighted the potential of two-stream architectures that integrate appearance and motio
arXiv:2604.14773v1 Announce Type: new Abstract: While LLMs have demonstrated remarkable potential in Question Answering (QA), evaluating personalization remains a critical bottleneck. Existing paradig
arXiv:2509.14255v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models improve efficiency through sparse activation, but their learned gating functions provide limited insight into routin