1 citations · 1 across the 12 of their papers we have counts for
16 papers
Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUT
M. Harper Langston, Pierre-David Letourneau, Dalton Jones +7
Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization. We study Particle Polynomial Relaxation (PPR), a…
Alleviating Hallucination in Reasoning Tasks with Training-Free Uncertainty-Guided Steering
Litian Liu, Qiqi Hou, Yubing Jian +5
Recent work on hallucination detection in large language models has shown that, for a fixed pre-trained model and reasoning task, it is possible to estimate the model's confidence…
On Locality and Length Generalization in Visual Reasoning
Pulkit Madan, Sanjay Haresh, Reza Ebrahimi +3
A striking feature of the human visual system is that it ingests visual information through a series of local foveated glimpses, rather than a single global computation. This makes…
Streaming Interventions: Can Video Large Language Models Correct Mistakes as They Occur?
Apratim Bhattacharyya, Shweta Mahajan, Sanjay Haresh +5
Learning everyday skills, like cooking a dish, relies increasingly on instructional media such as online videos. This opens the door to the use of video (and multimodal) large lang…
Notes-to-Self: Scratchpad Augmented VLAs for Memory Dependent Manipulation Tasks
Sanjay Haresh, Daniel Dijkman, Apratim Bhattacharyya +1
Many dexterous manipulation tasks are non-markovian in nature, yet little attention has been paid to this fact in the recent upsurge of the vision-language-action (VLA) paradigm. A…
From Out-of-Distribution Detection to Hallucination Detection: A Geometric View
Litian Liu, Reza Pourreza, Yubing Jian +2
Detecting hallucinations in large language models is a critical open problem with significant implications for safety and reliability. While existing hallucination detection method…
Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?
Apratim Bhattacharyya, Bicheng Xu, Sanjay Haresh +6
Multi-modal Large Language Models (LLM) have advanced conversational abilities but struggle with providing live, interactive step-by-step guidance, a key capability for future AI a…
Delayed Attention Training Improves Length Generalization in Transformer--RNN Hybrids
Buu Phan, Reza Ebrahimi, Sanjay Haresh +1
We study length generalization in sequence models on a composite problem involving both state tracking and associative recall. Prior work finds that recurrent networks handle state…
Can Vision-Language Models Answer Face to Face Questions in the Real-World?
Reza Pourreza, Rishit Dagli, Apratim Bhattacharyya +3
AI models have made significant strides in recent years in their ability to describe and answer questions about real-world images. They have also made progress in the ability to co…
Enhancing Hallucination Detection through Noise Injection
Litian Liu, Reza Pourreza, Sunny Panchal +4
Large Language Models (LLMs) are prone to generating plausible yet incorrect responses, known as hallucinations. Effectively detecting hallucinations is therefore crucial for the s…
ClevrSkills: Compositional Language and Visual Reasoning in Robotics
Sanjay Haresh, Daniel Dijkman, Apratim Bhattacharyya +1
Robotics tasks are highly compositional by nature. For example, to perform a high-level task like cleaning the table a robot must employ low-level capabilities of moving the effect…
AirLetters: An Open Video Dataset of Characters Drawn in the Air
Rishit Dagli, Guillaume Berger, Joanna Materzynska +2
We introduce AirLetters, a new video dataset consisting of real-world videos of human-generated, articulated motions. Specifically, our dataset requires a vision model to predict l…
Your Context Is Not an Array: Unveiling Random Access Limitations in Transformers
MohammadReza Ebrahimi, Sunny Panchal, Roland Memisevic
Despite their recent successes, Transformer-based large language models show surprising failure modes. A well-known example of such failure modes is their inability to length-gener…
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction
Sunny Panchal, Apratim Bhattacharyya, Guillaume Berger +10
Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, where each turn must be stepped (i.e…
Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving
Zhan Ling, Yunhao Fang, Xuanlin Li +5
Large Language Models (LLMs) have achieved tremendous progress, yet they still often struggle with challenging reasoning problems. Current approaches address this challenge by samp…
Look, Remember and Reason: Grounded reasoning in videos with language models
Apratim Bhattacharyya, Sunny Panchal, Mingu Lee +3
Multi-modal language models (LM) have recently shown promising performance in high-level reasoning tasks on videos. However, existing methods still fall short in tasks like causal…