When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors
While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e.,...
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While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e.,...
Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own co...
LLM agents increasingly act over long horizons, where a single trajectory can contain hundreds or thousands of action...
When does training language models (LMs) to generate explanations of their predictions yield faithful introspection, ...
On-policy distillation (OPD) offers superior capacity transfer by supervising student-sampled trajectories with dense...
Would experience designing faster GPU kernels also help close in on a long-standing open mathematical conjecture? Lar...
Audio-video generation has recently gained unprecedented research attention, aiming to synthesize high-quality soundi...
We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent s...
Video World Models are interactive video generation models that predict future world states based on user actions and...
Autoregressive Transformers dominate high-quality mesh generation by producing artist-worthy topologies, yet their in...
Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real appli...
Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in paralle...