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20142026
most citedWeighted Envy-Freeness in Indivisible Item Allocation

58 citations · 163 across the 32 of their papers we have counts for

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cs.AI2026

STRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks

ELita Lobo, Xu Chen, Jingjing Meng +5

Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behaviors that lead to premature termina…

cs.AI2023★ 3 cited

Axiomatic Aggregations of Abductive Explanations

Gagan Biradar, Yacine Izza, Elita Lobo +2

The recent criticisms of the robustness of post hoc model approximation explanation methods (like LIME and SHAP) have led to the rise of model-precise abductive explanations. For e…

cs.AI2020★ 29 cited

Finding Fair and Efficient Allocations When Valuations Don't Add Up

Nawal Benabbou, Mithun Chakraborty, Ayumi Igarashi +1

In this paper, we present new results on the fair and efficient allocation of indivisible goods to agents whose preferences correspond to {\em matroid rank functions}. This is a ve…

cs.AI2019★ 58 cited

Weighted Envy-Freeness in Indivisible Item Allocation

Mithun Chakraborty, Ayumi Igarashi, Warut Suksompong +1

We introduce and analyze new envy-based fairness concepts for agents with weights that quantify their entitlements in the allocation of indivisible items. We propose two variants o…

cs.AI2019★ 4 cited

A Learning Framework for Distribution-Based Game-Theoretic Solution Concepts

Tushant Jha, Yair Zick

The past few years have seen several works on learning economic solutions from data; these include optimal auction design, function optimization, stable payoffs in cooperative game…

cs.AI2017★ 12 cited

The Price of Quota-based Diversity in Assignment Problems

Nawal Benabbou, Mithun Chakraborty, Vinh Ho Xuan +2

We introduce and analyze an extension to the matching problem on a weighted bipartite graph: Assignment with Type Constraints. The two parts of the graph are partitioned into subse…

cs.AI2017

Axiomatic Characterization of Data-Driven Influence Measures for Classification

Jakub Sliwinski, Martin Strobel, Yair Zick

We study the following problem: given a labeled dataset and a specific datapoint x, how did the i-th feature influence the classification for x? We identify a family of numerical i…