All entries

Multimodal Taxonomic Conditioning for Generative Plankton Imagery

model-releasesarxiv-cs-cv

arXiv:2609.11673v1 Announce Type: new Abstract: Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or e

Content type

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Musec: MomentUm SpEctral Clipping for Stable Muon-type Training

DGX agent

arXiv:2609.11655v1 Announce Type: new Abstract: Muon has emerged as a highly effective optimizer for large language model training, often achieving superior convergence and performance compared with t

researcharxiv-cs-lg

11 Sept 2026

MUtE: A Dual Framework for Concept Erasure and Counterfactual Interventions

arXiv:2609.11253v1 Announce Type: cross Abstract: Erasing concept-specific information from representations has been proven useful for mitigating bias or interpreting model decisions. The joint object

safetyarxiv-cs-cl

Narrative Consolidation: Formulating a New Task for Unifying Multi-Perspective Accounts

arXiv:2512.18041v2 Announce Type: replace Abstract: Processing overlapping narrative documents, such as legal testimonies or historical accounts, often aims not for compression but for a unified, cohe

NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

arXiv:2609.10715v1 Announce Type: new Abstract: We introduce NCP-ArchPreview, a latent-space language model that pushes autoregressive pretraining beyond standard next-token prediction (NTP). Alongsid

Near-optimal estimates for the ell^p-Lipschitz constants of deep random ReLU neural networks

arXiv:2506.19695v2 Announce Type: replace-cross Abstract: This paper studies the ell^p-Lipschitz constants of ReLU neural networks Phi: R^d o R with random parameters for p in [1,infty]. The distribut

Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead

arXiv:2609.11807v1 Announce Type: cross Abstract: We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence o

agentsarxiv-cs-lg

Negative Self-Distillation: Learning to Reason by Avoiding Flaws

arXiv:2609.11699v1 Announce Type: new Abstract: On-Policy Self-Distillation (OPSD) has emerged as a popular paradigm for large language model (LLM) self-improvement, allowing models to act as their ow

safetyarxiv-cs-cl

New Evidence, Same Choice: Testing Physical Experiment Selection in Vision Language Models

arXiv:2609.11022v1 Announce Type: cross Abstract: A model first sees an image from one physical measurement experiment, such as how far a block coasted, and must answer a question about a new trial, s

Nice stats from @OpenRouter that illustrate how @togethercompute delivers solid and scaled performance for agentic workloads. We are serving…

Nice stats from @OpenRouter that illustrate how @togethercompute delivers solid and scaled performance for agentic workloads. We are serving GLM 5.3 and GLM 5.3 Flash @ top decile of TPS, latency, cac

agentstogether-ai--x

No Screening is More Efficient with Multiple Objects

arXiv:2408.10077v4 Announce Type: replace-cross Abstract: We study the welfare-maximizing allocation of heterogeneous objects when screening uses costly effort rather than monetary transfers. No-scree

Now live in LM Studio Bionic!

model-releaseslm-studio--x

Now live in LM Studio Bionic! 🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 D

Nuha-Speech: Building General-Purpose Arabic Speech-LLMs

arXiv:2609.11892v1 Announce Type: new Abstract: As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for

Numbat: Building and Verifying a Self-Contained Machine-Learning Stack

model-releasesarxiv-cs-lg

arXiv:2609.10632v1 Announce Type: cross Abstract: Machine-learning systems are built almost exclusively on a few large Python-orchestrated frameworks, and they inherit those stacks' engineering costs:

Hardware

Nvidia’s Backstop Universe – Heads I Win, Tails Who Loses?

The article examines Nvidia’s role in the 11 trillion AI infrastructure boom, exploring how the company finances this growth through AI Compute, Capital and Markets models that reveal funding sources,

hardwaresemianalysis

ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations

arXiv:2609.10918v1 Announce Type: cross Abstract: Imitation learning has achieved impressive results in robotic manipulation, yet most existing approaches assume clean backgrounds and lack explicit me

OmniHallu: Unified Hallucination Detection for Cross-Modal Comprehension and Generation in Multimodal Large Language Models

arXiv:2609.11244v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse tasks, they suffer from hallucinations where generated o

OmniKVQuant: KV Cache Quantization for Omni-LLMs

arXiv:2609.11582v1 Announce Type: new Abstract: As Omni-modal large language models (Omni-LLMs) take in audio, video and text together, their KV cache memory cost grows. KV cache quantization is the d

researcharxiv-cs-cv

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

researcharxiv-cs-cl

On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study

arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft

On the Societal Impact of Machine Learning

arXiv:2510.23693v2 Announce Type: replace Abstract: This PhD thesis investigates the societal impact of machine learning (ML). ML increasingly informs consequential decisions and recommendations, sign

One of the main issues with AI document parsing is that because no solution is 100% accuracy, it's hard to tell if a given page is parsed in…

One of the main issues with AI document parsing is that because no solution is 100% accuracy, it's hard to tell if a given page is parsed incorrectly: for instance a misaligned table, missing/hallucin

agentsjerry-liu--x

Industry

OpenAI says it's no longer sponsoring Caltech's math hackathon, where participants use AI to solve research problems, following criticism of 'slop mathematics' (Truman Dickerson/Business Insider)

Truman Dickerson / Business Insider: OpenAI says it's no longer sponsoring Caltech's math hackathon, where participants use AI to solve research problems, following criticism of “slop mathematics” — T

industrytechmeme

Industry

OpenAI targets Wall Street bankers with a new version of ChatGPT

OpenAI Group PBC is going after Wall Street with a new version of ChatGPT that’s tailor made for financial tasks such as analysis and calculations. Predictably called ChatGPT for Financial Services, i

industrysiliconangle

OpenDiscoveryTrace: Process Traces for Evaluating AI Scientist Workflows

model-releasesarxiv-cs-ai

arXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs---generated code, hypotheses, or papers---yet discard the reasoning process

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis

arXiv:2603.20278v2 Announce Type: replace-cross Abstract: Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. Howev

agentsarxiv-cs-cl

Optimizing AI Inference Across the Deployment Stack

model-releasesarxiv-cs-lg

arXiv:2609.10550v1 Announce Type: cross Abstract: AI deployment performance is shaped not by model architecture alone, but by interactions among compression, compiler transformations, and serving poli

Applications

Optimizing Three Critical Factors for Practical and Effective OOD Detection Fine-Tuning

arXiv:2308.01030v2 Announce Type: replace-cross Abstract: In out-of-distribution (OOD) detection, fine-tuning with auxiliary outlier data often improves detection performance at the cost of classifica

applicationsarxiv-cs-cv

ORCH: Organizational Principles Enable Collective Intelligence in Embodied AI

arXiv:2609.11737v1 Announce Type: cross Abstract: Collective intelligence depends not only on the capabilities of individual members, but also on how those members are organized. Yet artificial multi-

agentsarxiv-cs-lg

Order-Aware 2.5D Multiple Instance Learning for Preoperative MRI-Based Perineural Invasion Risk Assessment in Intrahepatic Cholangiocarcinoma

arXiv:2609.11271v1 Announce Type: new Abstract: Perineural invasion (PNI) is an adverse histopathologic marker in intrahepatic cholangiocarcinoma (ICC), but it is usually confirmed only after resectio

safetyarxiv-cs-cv

Local Ai

Orukeet, new ASR model based on Parakeet

I haven't seen this mentioned yet, so I thought it deserves a post. I was trying out OpenWhispr when this model came up as the recommendation. So I don't have personal experience yet, but it's suppose

local-air-localllama

Output Embedding Centering for Stable LLM Pretraining

arXiv:2601.02031v3 Announce Type: replace-cross Abstract: Pretraining of large language models is not only expensive but also prone to certain training instabilities. A specific instability that often

researcharxiv-cs-cl

Overpainting: Localized Context-aware Diffusion Image Editing

arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t

researcharxiv-cs-cv

Overview of the NLPCC 2026 Shared Task 11: Agent-Based Experiment Reproduction from Scientific Papers

arXiv:2609.11117v1 Announce Type: new Abstract: Reproducibility is essential to scientific progress, yet the growing volume and complexity of scientific publications make exhaustive manual verificatio

Pairit: A Platform for Live Experiments on Human-AI Collaboration

arXiv:2609.09789v1 Announce Type: cross Abstract: Organizational design in the era of artificial intelligence requires experimental methods that can test how human-AI groups coordinate, delegate, and

researcharxiv-cs-ai

Partial GFlowNet: Accelerating Convergence in Large State Spaces via Strategic Partitioning

arXiv:2602.11498v2 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets) have shown promising potential to generate high-scoring candidates with probability proportional to their rewar

Particle GFlowNets: Rethinking Generative Marginalization Models

arXiv:2609.11538v1 Announce Type: new Abstract: Generative Marginalization Models (MaMs) have been recently introduced as efficient neural sampling models for any-order autoregressive modelling of dis

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images

arXiv:2503.17970v2 Announce Type: replace-cross Abstract: Breast cancer survival prediction in computational pathology presents a remarkable challenge due to tumor heterogeneity. For instance, differe

researcharxiv-cs-cv

PEARL: A Task-Aware Framework for Evaluating Differentially Private Synthetic Educational Data

arXiv:2609.10612v1 Announce Type: cross Abstract: Personalized learning systems rely on real learner data, including performance, behavior, and demographic information, but these data are highly priva

Periodic robust robotic rock chop via virtual model control

arXiv:2508.02604v4 Announce Type: replace Abstract: Robotic cutting is a challenging, contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large conta

researcharxiv-cs-ro

Perturbation: A simple and efficient adversarial tracer for representation learning in language models

arXiv:2603.23821v2 Announce Type: replace Abstract: Linguistic representation learning in deep neural language models (LMs) has been studied for decades, but finding representations in LMs remains an

researcharxiv-cs-cl

Hardware

Phase-Decoupled, Model-Calibrated Power Control for Disaggregated LLM Serving

arXiv:2609.11133v1 Announce Type: new Abstract: Datacenter GPU power is the binding constraint on LLM serving capacity, and production serving has shifted to prefill/decode (PD) disaggregation. Deploy

hardwarearxiv-cs-lg

Phases in a class of associative memories via hidden neurons

model-releasesarxiv-cs-lg

arXiv:2609.10976v1 Announce Type: new Abstract: Associative memory in the Hopfield network is attractor dynamics in a disordered many-body system, and higher-order and exponential extensions turn its

PitchFlower: A flow-based neural audio codec with pitch controllability

arXiv:2510.25566v2 Announce Type: replace-cross Abstract: We present PitchFlower, a flow-based neural audio codec with explicit pitch controllability. Our approach promotes pitch disentanglement throu

Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers

arXiv:2609.10905v1 Announce Type: new Abstract: Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the config

researcharxiv-cs-ro

Polyhedral Geometry of Time-to-First-Spike Neural Networks

arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv

PRAGMA: Evaluating Personalized Guidance with Memory Alignment in Lifelong Conversations

model-releasesarxiv-cs-ai

arXiv:2609.09664v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as personalized assistants that interact with users over extended periods of time. As conversatio

Pre- and Post-Treatment Brain Metastases Segmentation Using nnU-Net with Post-Processing for BraTS 2026

model-releasesarxiv-cs-cv

arXiv:2609.11477v1 Announce Type: new Abstract: Brain metastases exhibit high inter-lesion variability in size, enhancement pattern, and post-treatment appearance, making volumetric segmentation of bo