6 citations · 41 across the 26 of their papers we have counts for
11 papers · 1 filter
dKFD: Phase-Structured Evidence Allocation for Fixed-Budget Localized Event Understanding
Aditya Bagri, Ashutosh Kumar, Chaitanya Lakhchaura +3
Sparse video understanding often requires selecting a small set of visual evidence under a fixed frame budget. Most sparse selectors allocate this budget globally, allowing all fra…
NutriVision: Ingredient-Conditioned Fusion and Prediction for Single-Image Food Nutrition Estimation
Aman Kumar, Avinash Anand, Chaitanya Lakhchaura +5
Nutrition estimation is a fundamental task in consumer diet tracking, clinical dietetics, chronic disease management, sports and hospital nutrition, and broader food computing syst…
SynDORBench: Evaluating LVLM Perceptual Robustness Under Physically Constrained Visibility Conditions
Jeremy Stephen Gabriel Yee, Zhengkui Wang, Zhiyuan Zhang +5
Large vision-language models (LVLMs) have demonstrated remarkable performance on multimodal reasoning benchmarks, yet their perceptual reliability under physically constrained imag…
How Do VLMs Fail? Vision-Operation Misalignment in Compositional VQA
Navya Gupta, Bingjie Xu, Avinash Anand +2
Compositional visual question answering requires Vision-Language Models (VLMs) to execute multiple reasoning operations like object selection, spatial relation resolution, and attr…
TextNCA: Neural Cellular Automata for Language Modeling via Hierarchical Local Attention
Avni Mittal, Avinash Anand, Ashutosh Kumar +7
Can a strictly local, iterated, weight-shared computation primitive support language modelling, and which of those three properties actually drives the model's behaviour? We define…
StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data
Akshat Parmar, Vikranth Udandarao, Abhay Shakya +4
StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured queries over real-world market dat…
FORGE: Fused On-Register Gradient Elimination for Memory-Efficient LLM Training
Dikshant Kukreja, Kritarth Prasad, Avinash Anand +6
Reverse-mode differentiation computes every weight gradient, writes it to memory, and only then lets the optimizer read it back. This two-phase schedule sets the memory ceiling of…
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes
Avinash Anand, Mahisha Ramesh, Avni Mittal +8
Reasoning has become central to how Large Language Models (LLMs) are evaluated and interpreted, spanning Chain-of-Thought (CoT), mathematical problem-solving, multi-hop question an…
Psychologically-Grounded Graph Modeling for Interpretable Depression Detection
Rishitej Reddy Vyalla, Kritarth Prasad, Avinash Anand +4
Automatic depression detection from conversational interactions holds significant promise for scalable screening but remains hindered by severe data scarcity and a lack of clinical…
IRIS: Interleaved Reinforcement with Incremental Staged Curriculum for Cross-Lingual Mathematical Reasoning
Navya Gupta, Rishitej Reddy Vyalla, Avinash Anand +8
Curriculum learning helps language models tackle complex reasoning by gradually increasing task difficulty. However, it often fails to generate consistent step-by-step reasoning, e…
Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size
Dikshant Kukreja, Kshitij Sah, Gautam Gupta +5
Larger language models become simultaneously better and worse at handling contextual information -- better at ignoring false claims, worse at ignoring irrelevant tokens. We formali…