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Found 9 papers, 5 papers with code
Tools Fail: Detecting Silent Errors in Faulty Tools
Tools have become a mainstay of LLMs, allowing them to retrieve knowledge not in their weights, to perform tasks on the web, and even to control robots.
DiffusionPID: Interpreting Diffusion via Partial Information Decomposition
Text-to-image diffusion models have made significant progress in generating naturalistic images from textual inputs, and demonstrate the capacity to learn and represent complex visual-semantic relationships.
Language Models Need Inductive Biases to Count Inductively
We find that while traditional RNNs trivially achieve inductive counting, Transformers have to rely on positional embeddings to count out-of-domain.
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
We validate our approach for various linear inverse problems, such as super-resolution, deblurring, inpainting, and compressed sensing, and demonstrate that we can outperform other methods based on flow matching.
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation
We hypothesize that the underlying phenomenological coverage has not been proportionally scaled up, leading to a skew of the presented phenomenon which harms generalization.
VISREAS: Complex Visual Reasoning with Unanswerable Questions
The unique feature of this task, validating question answerability with respect to an image before answering, and the poor performance of state-of-the-art models inspired the design of a new modular baseline, LOGIC2VISION that reasons by producing and executing pseudocode without any external modules to generate the answer.
Toxicity Detection with Generative Prompt-based Inference
It is a long-known risk that language models (LMs), once trained on corpus containing undesirable content, have the power to manifest biases and toxicity.
Training Vision-Language Transformers from Captions
Vision-Language Transformers can be learned without low-level human labels (e. g. class labels, bounding boxes, etc).
WebQA: Multihop and Multimodal QA
Scaling Visual Question Answering (VQA) to the open-domain and multi-hop nature of web searches, requires fundamental advances in visual representation learning, knowledge aggregation, and language generation.
