Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Qwen-AgentWorld: Language World Models for General Agents

arxiv.org

Post reply on HN
Print view View original

11–20 of 65 posts

Re: Qwen-AgentWorld: Language World Models for General Agents

#11

Post by Tepix »

dudisubekti wrote: post #7
Tepix wrote: post #4

The labels of the very first chart (figure 1, bottom left) are obviously wrong which casts a doubt on the entire paper.

This label? > Figure 1: Overview of Qwen-AgentWorld. Top: Qwen-AgentWorld is a unified native language world model across seven domains. Bottom: We explore two complementary strategies for applying world modeling to enhance language agents (mainly using the 35B-A3B model as agent): Decouple and Unify , where the world model serves as the environment simulator and agent foundation model, respectively. Where is the mis…

The deltas are wrong.

The bars above the label "Infinite Real-World Envs" show growth for example from approx 42 to 55 but the red label says "+7.1". It's wrong for all of them.

Re: Qwen-AgentWorld: Language World Models for General Agents

#12

Post by [deleted] »

Tepix wrote: post #11
dudisubekti wrote: post #7

Earlier quoted context omitted.

This label? > Figure 1: Overview of Qwen-AgentWorld. Top: Qwen-AgentWorld is a unified native language world model across seven domains. Bottom: We explore two complementary strategies for applying world modeling to enhance language agents (mainly using the 35B-A3B model as agent): Decouple and Unify , where the world model serves as the environment simulator and agent foundation model, respectively. Where is the mis…

The deltas are wrong. The bars above the label "Infinite Real-World Envs" show growth for example from approx 42 to 55 but the red label says "+7.1". It's wrong for all of them.

[deleted]

Re: Qwen-AgentWorld: Language World Models for General Agents

#14

Post by yorwba »

Tepix wrote: post #11
dudisubekti wrote: post #7

Earlier quoted context omitted.

This label? > Figure 1: Overview of Qwen-AgentWorld. Top: Qwen-AgentWorld is a unified native language world model across seven domains. Bottom: We explore two complementary strategies for applying world modeling to enhance language agents (mainly using the 35B-A3B model as agent): Decouple and Unify , where the world model serves as the environment simulator and agent foundation model, respectively. Where is the mis…

The deltas are wrong. The bars above the label "Infinite Real-World Envs" show growth for example from approx 42 to 55 but the red label says "+7.1". It's wrong for all of them.

According to Table 6, it's supposed to be 47.9 to 55.

Re: Qwen-AgentWorld: Language World Models for General Agents

#18

Post by blourvim »

aliljet wrote: post #15

The benchmarks here are confusing at best. Am I reading correctly that this model is essentially as good or better than all frontier models right now?

Benchmarks in general are a little iffy, the whole industry is going off of vibes anyways. Can't decide before trying it out

Re: Qwen-AgentWorld: Language World Models for General Agents

#19

Post by anana_ »

aliljet wrote: post #15

The benchmarks here are confusing at best. Am I reading correctly that this model is essentially as good or better than all frontier models right now?

I believe the benchmark listed is about simulating the environment for the various tasks, rather than doing them. It seems that the point of this model is to generate sim data to improve other models with

Re: Qwen-AgentWorld: Language World Models for General Agents

#20

Post by dmos62 »

gavmor wrote: post #8
psc007 wrote: post #6

Eli5? What is this compared to a regular llm assistant model like the base qwen?

A regular LLM acts as a "policy," mapping a current state to a specific action (states → actions). Their new LLM acts as a "world model," mapping a current state and a chosen action to a predicted future state ((states, actions) → subsequent states). Instead of deciding "what to do," its explicit objective is to predict the exact environment observation that will result from the interaction history and the agent's cu…

So, if I'm reading this correctly, whereas a regular LLM would, given a prompt to edit a file, infer a sed call, this "world" model infers the resulting contents of the file.
Post reply on HN