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Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations
With models like AlphaFold3 limited to academic research, the team built an equivalent alternative, to encourage innovation more broadly.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.
An NVIDIA research team proposes Hymba, a family of small language models that blend transformer attention with state space models, which outperforms the Llama-3.2-3B model with a 1.32% higher average accuracy, while reducing cache size by 11.67× and increasing throughput by 3.49×.
The post NVIDIA’s Hybrid: Combining Attention and State Space Models for Breakthrough Performance of Small Language Models first appeared on Synced.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
In a new paper Time-Reversal Provides Unsupervised Feedback to LLMs, a research team from Google DeepMind and Indian Institute of Science proposes Time Reversed Language Models (TRLMs), a framework that allows LLMs to reason in reverse—scoring and generating content in a manner opposite to the traditional forward approach.
The post From Response to Query: The Power of Reverse Thinking in Language Models first appeared on Synced.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.
A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.
Using LLMs to convert machine-learning explanations into readable narratives could help users make better decisions about when to trust a model.
In a new paper Navigation World Models, a research team from Meta, New York University and Berkeley AI Research proposes a Navigation World Model (NWM), a controllable video generation model that enables agents to simulate potential navigation plans and assess their feasibility before taking action.
The post Yann LeCun Team’s New Research: Revolutionizing Visual Navigation with Navigation World Models first appeared on Synced.