Knowledge catalogue
arXiv:2609.26086v1 Announce Type: new Abstract: An agentic retrieval system issues a sequence of search queries and must decide, at each step, whether the evidence collected so far is enough to stop.
arXiv:2609.23142v1 Announce Type: new Abstract: Building gameplay features in a game engine requires more than code, as code that compiles and runs does not necessarily implement the requested gamepla
Hey everyone! I've been experimenting with Qwen Image 2.1 Prompt Enhancer (PE) lately and noticed an interesting detail in Qwen's official system prompts. The PE models output structured JSON containi
arXiv:2609.24369v1 Announce Type: cross Abstract: Deception plays a central role in Intelligence operations, yet it remains difficult to analyse systematically without expert knowledge of reasoning pa
arXiv:2609.26502v1 Announce Type: cross Abstract: Deep generative models are widely reported to enable de novo crystal structure prediction (CSP), but their capability has not been measured consistent
arXiv:2609.25397v1 Announce Type: new Abstract: The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and
The rumor about Kimi execs getting arrested finally has some legs. I believe the reality is more like under investigation for potential arrests or fine. submitted by /u/Ok_Warning2146 [link] [comments
arXiv:2609.26638v1 Announce Type: new Abstract: Autoregressive OCR vision-language models accurately convert document images into text and structured markup, but require one sequential decoding step p
arXiv:2609.26737v1 Announce Type: cross Abstract: Detection of overlapping communities is essential for modelling networks in which nodes participate simultaneously in multiple structural or functiona
arXiv:2609.25429v1 Announce Type: new Abstract: In this paper, we introduce the Directional Total Variation-Regularized Implicit Neural Representation (DTV-INR), an advanced variational paradigm that
arXiv:2609.26333v1 Announce Type: new Abstract: Prefill and decode reward different approaches to quantization: low-precision arithmetic accelerates prompt processing, while compact weights reduce mem
arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u
arXiv:2609.23201v1 Announce Type: new Abstract: Benchmark scores increasingly influence the development, marketing, and selection of large language models (LLMs). Yet an overall score is interpretable
arXiv:2609.25010v1 Announce Type: cross Abstract: Marketers increasingly use large language models (LLMs) as 'synthetic personas' to predict how an audience will react to a piece of copy before it shi
arXiv:2609.24092v1 Announce Type: new Abstract: Real-world document processing systems rely on rigid, predefined schemas, yet critical target fields often lack direct visual counterparts on the page.
arXiv:2609.26034v1 Announce Type: new Abstract: Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature. T
arXiv:2609.26792v1 Announce Type: new Abstract: Faithfully evaluating end-to-end driving policies in simulation requires observations that are not merely photo-realistic, but preserve the scene featur
arXiv:2609.26121v1 Announce Type: cross Abstract: As agent capabilities have grown, practical limitations increasingly stem from constrained context windows rather than model capacity. Common strategi
arXiv:2609.25149v1 Announce Type: new Abstract: Solving large-scale instances of the Traveling Salesman Problem (TSP) exactly is computationally expensive. Researchers often employ graph sparsificatio
arXiv:2609.24662v1 Announce Type: new Abstract: LLM-based agents increasingly operate in environments where they interact with users, tools, and external systems. Yet most security evaluations assume
arXiv:2609.22775v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer a promising path toward ultra-low-power artificial intelligence inference by emulating the event-driven computation
arXiv:2609.24115v1 Announce Type: new Abstract: Tool-calling LLM agents are increasingly deployed in enterprise applications. However, effective evaluation and optimization require high-quality, diver
arXiv:2609.25645v1 Announce Type: cross Abstract: Exhaustively evaluating every candidate LLM configuration on every benchmark item to identify a high-performing one is costly. We formulate configurat
arXiv:2609.25405v1 Announce Type: cross Abstract: Modern information retrieval increasingly employs both embedding and generative models to handle complex queries. However, current serving systems suf
arXiv:2609.25582v1 Announce Type: new Abstract: Public surface electromyography (EMG) datasets vary widely in electrode layout, channel count, frequency support, and size. Simply mixing them for pretr
Update from : https://old.reddit.com/r/LocalLLaMA/comments/1wis23s/update_small_model_engram/ It's been about a week so I'm back. People were asking me about the model. People wanted code, or models,
arXiv:2606.19980v2 Announce Type: replace Abstract: Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bo
arXiv:2609.26422v1 Announce Type: new Abstract: Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans. Speech Emotion Recognition (SER) has becom
arXiv:2609.26751v1 Announce Type: new Abstract: Large language models are increasingly used to generate SystemVerilog Assertions from natural-language specifica- tions and register-transfer-level desi
arXiv:2609.26326v1 Announce Type: cross Abstract: We study preference elicitation under the Bradley-Terry-Luce (BTL) model where the true partworth vector is unknown and has to be estimated as a param
arXiv:2609.24927v1 Announce Type: new Abstract: Personal AI agents make recommendations and take actions on people's behalf in high-stakes economic contexts, e.g., buying a flight, choosing health ins
arXiv:2609.25788v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing wor
arXiv:2609.25876v1 Announce Type: new Abstract: The connection between the Kolmogorov-Arnold representation theorem (KART) and neural network design has led to the development of Kolmogorov-Arnold Net
arXiv:2609.25615v1 Announce Type: new Abstract: Architectural floor plans remain a high-friction barrier to archive digitization and early design-model preparation because heterogeneous graphics encod
Exciting work from NVIDIA. (bookmark it) Interesting to see this approach to turn public Agent Skills into RL environments. Lots of excitement around RL environments so this is a great read. Skill2Env
arXiv:2605.06368v2 Announce Type: replace-cross Abstract: Despite extensive research into mitigating distribution shifts, many existing algorithms yield inconsistent performance, often failing to outp
arXiv:2609.25152v1 Announce Type: new Abstract: Deep Imbalanced Regression (DIR) addresses a common failure mode of regression models: target distributions are highly non-uniform, causing models to pe
arXiv:2609.25505v1 Announce Type: cross Abstract: Rapid intensification (RI) remains one of the most consequential and difficult aspects of tropical cyclone (TC) forecasting. Although full-physics num
arXiv:2609.25082v1 Announce Type: new Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-fro
arXiv:2609.25298v1 Announce Type: new Abstract: Cultural evaluation coverage and robustness in language models are difficult to diagnose because pretraining corpora and cultural benchmarks are rarely
arXiv:2609.25192v1 Announce Type: new Abstract: Financial search is a highly demanding task for LLM agents, requiring not only a correct final answer but also temporally valid information retrieval, a
arXiv:2609.24002v1 Announce Type: new Abstract: Large language model agents increasingly answer financial questions by searching regulatory filings. Such questions are often deceptively under-specifie
arXiv:2609.26048v1 Announce Type: cross Abstract: Language-model agents often reach a working solution and then fail to consistently deliver it. We study runtime policies: targeted natural-language in
arXiv:2609.23064v1 Announce Type: new Abstract: Understanding the physical world requires more than object recognition, scene description, and short-term visual prediction, as real-world physical syst
For the last several years, I have said that OpenAI models are better at ideation, creation, and exploration. If I had to brainstorm something, I would have picked whatever OpenAI model was best in cl
arXiv:2609.22664v1 Announce Type: cross Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or repro
arXiv:2609.22719v1 Announce Type: cross Abstract: Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration
arXiv:2609.25655v1 Announce Type: new Abstract: As large language models (LLMs) scale rapidly, dense full-parameter adaptation becomes increasingly expensive, motivating sparse and modular architectur
arXiv:2609.22822v1 Announce Type: cross Abstract: We present Hybrid Quantum Root Cause Analysis (HQ-RCA), an industrially grounded workflow for root cause analysis in banking IT operations, built on a
arXiv:2609.23130v1 Announce Type: new Abstract: Large language model (LLM) inference is evolving from an engine-local optimization problem into a distributed control problem involving reusable state,
arXiv:2609.25625v1 Announce Type: new Abstract: Most minimally invasive surgery is still performed with hand-held laparoscopic instruments, and the surgeon's instrument kinematics are lost when the op
arXiv:2609.25669v1 Announce Type: new Abstract: Adoption and diffusion of neologisms in online communities have received renewed attention in recent years. As internet slang terms such as APT, referri
arXiv:2609.25050v1 Announce Type: new Abstract: We introduce FrontierMath Erdos (FME), a benchmark of 68 Erdos problems that are open as of August 2026. To solve a task in FME, AI systems must resolve
arXiv:2609.26067v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions, increasing flexibility but also parameter memory bec
arXiv:2609.26095v1 Announce Type: cross Abstract: With the growing global demand for energy, nuclear fusion has emerged as a promising direction for future clean energy. Tokamaks represent one of the
Tool: Gemini 3.8 TTS Playground Google released two new Gemini text-to-speech models today - gemini-3.8-flash-tts and gemini-3.8-flash-lite-tts. They come with a library of over 2,000 voices, plus the
Hey there folks! Aritra here from Hugging Face. I wanted to update you all about the latest changes in `transformers`. We now natively support GGUFs (llama cpp quants). You can use it like so: from tr
glance-vlm speedlab is now open source! read: https://glance.yohei.me/speed/ try: https://github.com/yoheinakajima/glance-speedlab turn any webcam into multiple live AI detectors (emotion, count, obje
arXiv:2507.14077v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) algorithms are a critical part of state-of-the-art digital health technology for diabetes management. Yet, access
Laura Bratton / The Information: Google DeepMind SVP Koray Kavukcuoglu says Gemini 4 is in the early phase of post-training and hopes it will be released “much earlier” than the end of the year — Goog