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30 results for "bot model"

ARXIV.ORG

Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition

Concept Bottleneck Models (CBMs) predict through human-interpretable concepts, but they typically output point concept probabilities that conflate epistemic uncertainty (reducible model underspecifica…

· 4 views
ARXIV.ORG

Evaluating whether AI models would sabotage AI safety research

We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier AI company. We apply two complementary evaluati…

· 4 views
TECHMEME

Xiaomi open sources MiMo-V2.5 and MiMo-V2.5-Pro under the MIT License, saying both models are among the most efficient available for agentic "claw" tasks (Carl Franzen/VentureBeat)

Carl Franzen / VentureBeat : Xiaomi open sources MiMo-V2.5 and MiMo-V2.5-Pro under the MIT License, saying both models are among the most efficient available for agentic “claw” tasks — Xiaomi, the Chi…

· 24 views
REDDIT

Why the VLA architecture is the real bottleneck keeping robots out of your home, and what a unified model might change

I've been following embodied intelligence research for a few years now, and something clicked for me recently about why we keep seeing incredible lab demos of robots folding laundry or making coffee, …

· 7 views
ARXIV CS.AI

MetaEarth3D: Unlocking World-scale 3D Generation with Spatially Scalable Generative Modeling

Recent generative AI models have achieved remarkable breakthroughs in language and visual understanding. However, although these models can generate realistic visual content, their spatial scale remai…

· 4 views
ARXIV CS.AI

Probing Visual Planning in Image Editing Models

Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in machine learning, this inherently visual problem is…

· 4 views
NATURE

'World models' are AI's latest sensation: what are they and what can they do?

Training AI world models on data about physical environments could improve their real-world capabilities in technologies such as robotics.…

· 4 views
KOREA TIMES

Robot dogs with Musk and Zuckerberg heads roam around Berlin gallery in Beeple's new exhibit

Robot dogs with hyper-realistic silicone heads modeled after world-renowned figures — including Elon Musk, Mark Zuckerberg, Jeff Bezos, Andy Warhol...…

· 12 views
ABC NEWS: INTERNATIONAL

Robot dogs with Musk and Zuckerberg heads roam Berlin gallery in Beeple's new exhibit

Robot dogs with hyper-realistic silicone heads modeled after famous figures like Elon Musk and Mark Zuckerberg are roaming a Berlin gallery…

· 12 views
STABLEDIFFUSION

Meta is about to release a pixel space model (Tuna-2)

There's a catch, though, they break it on purpose and want you to fix it: "Due to organizational policy constraints, we are unable to release the full production-trained model weights. To support the …

· 8 views
LOCALLLAMA

Do the "*Claude-4.6-Opus-Reasoning-Distilled" really bring something new to the original models?

No offense to the fine-tune model providers, just curious. IMO the original models were already trained on massive amount of high quality data, so why bother with this fine-tune? Just to make the mode…

· 6 views
ROBBYANT 蚂蚁灵波科技

LingBot-Map: Streaming 3D reconstruction with geometric context transformer

Technology-driven and application-oriented. We build foundational large models for embodied AI: spatial perception (LingBot-Depth), VLA (LingBot-VLA), world models (LingBot-World), video action (LingB…

· 5 views
SIMON WILLISON'S WEBLOG

Introducing talkie: a 13B vintage language model from 1930

Introducing talkie: a 13B vintage language model from 1930 New project from Nick Levine , David Duvenaud , and Alec Radford (of GPT, GPT-2, Whisper fame). talkie-1930-13b-base (53.1 GB) is a "13B lang…

· 6 views
ARXIV.ORG

Ulterior Motives: Detecting Misaligned Reasoning in Continuous Thought Models

Chain-of-Thought (CoT) reasoning has emerged as a key technique for eliciting complex reasoning in Large Language Models (LLMs). Although interpretable, its dependence on natural language limits the m…

· 3 views
ARXIV.ORG

Modeling Induced Pleasure through Cognitive Appraisal Prediction via Multimodal Fusion

Multimodal affective computing analyzes user-generated social media content to predict emotional states. However, a critical gap remains in understanding how visual content shapes cognitive interpreta…

· 3 views
ARXIV.ORG

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid advancement of Vision…

· 5 views
ARXIV.ORG

A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees

Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain expertise. Recently, Large Language Model (LLM)-b…

· 4 views
ARXIV.ORG

A systematic evaluation of vision-language models for observational astronomical reasoning tasks

Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astronomical observations across diverse modalities r…

· 6 views
ARXIV.ORG

Microsoft TRELLIS.2: An Open-Source, 4B-Parameter, Image-to-3D Model [pdf]

Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, which struggle to capture assets with com…

· 5 views
REDDIT

Speculative Decoding Implementations: EAGLE-3, Medusa-1, PARD, Draft Models, N-gram and Suffix Decoding from scratch

I’ve been working on an educational implementation repo for speculative decoding: The goal is not to wrap existing libraries, but to implement several speculative decoding methods from scratch behind …

· 8 views
REDDIT

Speculative Decoding Implementations: EAGLE-3, Medusa-1, PARD, Draft Models, N-gram and Suffix Decoding from scratch [P]

I’ve been working on an educational implementation repo for speculative decoding: The goal is not to wrap existing libraries, but to implement several speculative decoding methods from scratch behind …

· 9 views
NEW YORK POST

Bizarre robot dogs sporting Musk, Zuckerberg heads torment visitors in Berlin museum — as part of creepy influencer exhibit

The cyborg canines are all fitted with hyper-realistic silicone heads modeled after Mark Zuckerberg, Jeff Bezos, Pablo Picasso, and other modern industry leaders.…

· 12 views
ARXIV CS.AI

Can Current Agents Close the Discovery-to-Application Gap? A Case Study in Minecraft

Discovering causal regularities and applying them to build functional systems--the discovery-to-application loop--is a hallmark of general intelligence, yet evaluating this capacity has been hindered …

· 4 views
ARXIV CS.AI

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges regarding time, cost, and respondent fatigue. To addr…

· 4 views
ARXIV CS.AI

Behavioral Intelligence Platforms: From Event Streams to Autonomous Insight via Probabilistic Journey Graphs, Behavioral Knowledge Extraction, and Grounded Language Generation

Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, before insights can surface. This pull-based paradi…

· 4 views
ARXIV CS.AI

KARL: Mitigating Hallucinations in LLMs via Knowledge-Boundary-Aware Reinforcement Learning

Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucinations. While existing reinforcement learning methods f…

· 4 views
ARXIV CS.AI

BiTA: Bidirectional Gated Recurrent Unit-Transformer Aggregator in a Temporal Graph Network Framework for Alert Prediction in Computer Networks

Proactive alert prediction in computer networks is critical for mitigating evolving cyber threats and enabling timely defensive actions. Temporal Graph Neural Networks (TGNs) provide a principled fram…

· 3 views
ARXIV CS.AI

Applied AI-Enhanced RF Interference Rejection

AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on both the signal of interest (SOI) and the signal mi…

· 4 views
ARXIV CS.AI

WeatherSeg: Weather-Robust Image Segmentation using Teacher-Student Dual Learning and Classifier-Updating Attention

WeatherSeg, an advanced semi-supervised segmentation framework, addresses autonomous driving's environmental perception challenges in adverse weather while reducing annotation costs. This framework in…

· 4 views
ARXIV CS.AI

ParkingScenes: A Structured Dataset for End-to-End Autonomous Parking in Simulation Scenes

Autonomous parking remains a critical yet challenging task in intelligent driving systems, particularly within constrained urban environments where maneuvering space is limited and precise control is …

· 4 views