Search: “models”

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:2604.15760v1 Announce Type: new Abstract: We introduce the first version of KWBench (Knowledge Work Bench), a benchmark for unprompted problem recognition in large language models: can an LLM id

literally my basic model since 1998. crazy that some people still haven’t figured this out. My basic model of capabilities: LLMs are good at problems similar to those that appear in their training dat

arXiv:2604.15314v1 Announce Type: cross Abstract: This research aimed to develop an intelligent system to evaluate performance and extract behavioral models for children with ASD and neurotypical (TD)

Nice paper combining the strength of Skills and RAG. Most RAG systems retrieve on every query, whether the model needs help or not. This is wasteful when the model already knows the answer, and often

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

opus 4.7 dropped last week with two new features: xhigh effort: more compute when you need it task budgets: the model knows its limit and wraps up gracefully, this is a great example of giving the mod

Our researchers are heading to ICLR with new work: model efficiency, long-context reasoning, next-gen attention and decoding, and more. Check out what we've been building 👇🏼 #TogetherResearch #AINativ

arXiv:2512.06987v2 Announce Type: replace Abstract: Accurately predicting experimentally realizable 3D molecular crystal structures from their 2D chemical graphs is a long-standing open challenge in c

arXiv:2604.15483v1 Announce Type: new Abstract: We present a new robotic foundation model, called {pi}_{0.7}, that can enable strong out-of-the-box performance in a wide range of scenarios. {pi}_{0.7}

arXiv:2604.15670v1 Announce Type: new Abstract: Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including obliq

arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b

arXiv:2602.05638v3 Announce Type: replace Abstract: While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that w

arXiv:2604.13812v1 Announce Type: new Abstract: Quantum circuit optimization is a central task in Quantum Computing, as current Noisy Intermediate Scale Quantum devices suffer from error propagation t

arXiv:2510.24538v2 Announce Type: replace Abstract: Textual humor is enormously diverse and computational studies need to account for this range, including intentionally bad humor. In this paper, we c

arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these

arXiv:2604.15109v1 Announce Type: new Abstract: Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent a

arXiv:2512.05024v3 Announce Type: replace-cross Abstract: As generative AI models are increasingly used to simulate real-world systems, quantifying the ``sim-to-real'' gap is critical. For each input

arXiv:2604.14808v1 Announce Type: new Abstract: Machine unlearning for large language models (LLMs) aims to remove targeted knowledge while preserving general capability. In this paper, we recast LLM

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

Luz Ding / Bloomberg: Alibaba's new Token Hub unit releases Happy Oyster, a new AI world model that can create 3D environments, interactive videos, films, video content, and games — Alibaba Group Hold

arXiv:2512.02697v3 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images that visually correspond to a query image. However, the trad

arXiv:2604.13977v1 Announce Type: new Abstract: Synthetic data is a standard component in training large language models, yet systematic comparisons across design dimensions, including rephrasing stra

GPT-Rosalind is a frontier reasoning model developed by OpenAI, specifically designed to support research applications in biology, drug discovery, and translational medicine. The model was introduced

arXiv:2604.13386v1 Announce Type: new Abstract: Linear probes can detect when language models produce outputs they 'know' are wrong, a capability relevant to both deception and reward hacking. However

arXiv:2510.05056v2 Announce Type: replace Abstract: As programmers write code, they often edit and retry multiple times, creating rich 'interaction traces' that reveal how they approach coding tasks a

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

Nous Research is promoting their subscription portal and providing instructions for users to update and configure their Hermes model through command-line tools (`hermes update` and `hermes model`). Th

arXiv:2604.12777v1 Announce Type: cross Abstract: The human brain constructs emotional percepts not by processing facial expressions in isolation, but through a dynamic, hierarchical integration of se

arXiv:2604.12180v1 Announce Type: cross Abstract: Tropical cyclones (TCs) rank among the most destructive natural hazards, yet their forecasting faces fundamental trade-offs: numerical weather predict

arXiv:2604.12250v1 Announce Type: new Abstract: This study examines how model-specific characteristics of Large Language Model (LLM) agents, including internal alignment, shape the effect of memory on

arXiv:2508.12260v5 Announce Type: replace Abstract: Infectious disease forecasting in novel outbreaks or low-resource settings is hampered by the need for large disease and covariate data sets, bespok

Microsoft Corp.’s push for artificial intelligence independence is gaining traction with today’s release of MAI-Image-2-Efficient, a lean and mean version of its flagship image generation model that d

arXiv:2604.00136v2 Announce Type: replace-cross Abstract: Multi-model LLM serving operates in a non-stationary, noisy environment: providers revise pricing, model quality can shift or regress without

arXiv:2412.07238v3 Announce Type: replace Abstract: The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and

arXiv:2604.09617v1 Announce Type: new Abstract: Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for ge

arXiv:2604.10950v1 Announce Type: new Abstract: Fully supervised Video Semantic Segmentation (VSS) relies heavily on densely annotated video data, limiting practical applicability. Alternatively, appl

arXiv:2604.07716v2 Announce Type: replace Abstract: We present FDM (Fan Duality Model), a linear sequence architecture that resolves the fundamental tension between memory efficiency and associative r

arXiv:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor

arXiv:2310.17245v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) aims to optimize a policy using collected data without online interactions. Model-based approaches are par

arXiv:2604.10660v1 Announce Type: cross Abstract: Recent research has devoted considerable effort to verifying the intermediate reasoning steps of chain-of-thought (CoT) trajectories using process rew

arXiv:2604.10455v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled promising progress in diagnosis prediction from electronic health records (EHRs). However,

arXiv:2602.10042v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability

arXiv:2412.20704v2 Announce Type: replace Abstract: Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-genera

arXiv:2604.11549v1 Announce Type: cross Abstract: In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding

This Reddit thread addresses a common challenge for non-developers trying to run a local agentic coding assistant on a MacBook Air M5: while tools like Ollama, VS Code, and OpenCode are the right piec