May 2025 - talks - lists.cs.princeton.edu

Meenal Parakh will present her General Exam "AnyBody: A Benchmark Suite for Cross-Embodiment Manipulation" on Tuesday, May 6, 2025 at 4:30 PM in FC 202.
by CS Grad Department 01 May '25

01 May '25

Meenal Parakh will present her General Exam "AnyBody: A Benchmark Suite for Cross-Embodiment Manipulation" on Tuesday, May 6, 2025 at 4:30 PM in FC 202. Committee Members: Jia Deng (advisor), Szymon Rusinkiewicz, Adam Finkelstein Abstract: Generalizing control policies to novel embodiments remains a fundamental challenge in enabling scalable and transferable learning in robotics. While prior works have explored this in locomotion, a systematic study in the context of manipulation tasks remains limited, partly due to the lack of standardized benchmarks. In this paper, we introduce a benchmark for learning cross-embodiment manipulation, focusing on two foundational tasks, reach and push, across a diverse range of morphologies. The benchmark is designed to test generalization along three axes: interpolation (testing performance within a robot category, sharing the same link structure), extrapolation (testing on a robot with a different link structure), and composition (testing on combinations of link structure). We primarily test RL agents trained under multitask objectives and evaluated for their multi-task performance and zero-shot transfer. Our study aims to answer whether morphology-randomized training can outperform single-embodiment baselines, whether zero-shot generalization to unseen morphologies is feasible, and how consistently these patterns hold across different generalization regimes. The results highlight the current limitations of multi-embodiment learning and provide insights into how architectural and training design choices influence policy generalization. Reading List: https://docs.google.com/document/d/1Ey-U4ydkMTrTO6Qdr9FmycVom5daALctNbeyRjw… Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.

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Xingyu Zhu will present his General Exam "On the Power of Context-Enhanced Learning in LLMs" on Monday, May 5, 2025 at 1:00 PM in FC 106 and via zoom.
by CS Grad Department 01 May '25

01 May '25

Xingyu Zhu will present his General Exam "On the Power of Context-Enhanced Learning in LLMs" on Monday, May 5, 2025 at 1:00 PM in FC 106 and via zoom. Zoom link: https://princeton.zoom.us/my/jupiter Committee Members: Sanjeev Arora (advisor), Danqi Chen, Chi Jin Abstract: We formalize a new concept for LLMs, context-enhanced learning. It involves standard gradient-based learning on text except that the context is enhanced with additional data on which no auto-regressive gradients are computed. This setting is a gradient-based analog of usual in-context learning (ICL) and appears in some recent works. Using a multi-step reasoning task, we prove in a simplified setting that context-enhanced learning can be exponentially more sample-efficient than standard learning when the model is capable of ICL. At a mechanistic level, we find that the benefit of context-enhancement arises from a more accurate gradient learning signal. We also experimentally demonstrate that it appears hard to detect or recover learning materials that were used in the context during training. This may have implications for data security as well as copyright. Reading List: https://docs.google.com/document/d/1_SYs1g8A9cSF__u9dRffQ30ZYAArjijfiyW-IwV… Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.

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Amrit Daswaney will present the General Exam "Fair and Efficient Allocation of Indivisible Goods via Pseudomarkets with Price Floors" on May 2nd, 10 am - 12 pm. Friend Center 005.
by Gradinfo 01 May '25

01 May '25

Amrit Daswaney will present the General Exam "Fair and Efficient Allocation of Indivisible Goods via Pseudomarkets with Price Floors" on May 2nd, 10 am - 12 pm. Friend Center 005. Committee: Mark Braverman (adviser), Matt Weinberg, Fedor Sandomirskiy. Abstract: The combinatorial assignment problem involves allocating m indivisible goods to n agents without any monetary transfers such that the resulting allocation is Pareto efficient and each agent is (approximately) envy-free. This problem models many practical settings of interest: from assigning courses to students to allocating truckloads of food to food banks. A classical route, pioneered by Varian (1974) and extended by Hylland and Zeckhauser (1979), is to search for a Competitive Equilibrium from Equal Incomes (CEEI): endow every agent with one unit of artificial currency and find prices so that when each agent buys their favourite affordable bundle, the market clears (i.e., supply equals demand for all goods). With indivisible goods, however, a CEEI need not exist: in a two-agent, one-good instance any price makes either both agents or neither demand the good. Budish (2011) restores existence by introducing an arbitrarily small budget inequality between agents. The rationale behind introducing this budget inequality is to use these small differences to break ties between otherwise identical agents. However, our first result shows they can legitimize highly unequal outcomes, allowing agents with negligibly higher budgets to potentially leverage this advantage across multiple goods. To mitigate this, we introduce price floors and define a CEEI-with-price-floors mechanism. Our second result proves that this concept is equivalent to a discrete analogue of Varian (1974)'s coalition fairness: in the replica economy, no coalition can seize the bundle of another coalition with the same total endowment and make all of its members better off. The equivalence echoes the Debreu–Scarf core-equivalence theorem (1963). Crucially, whenever a CEEI-with-floors can be proved to exist for a structured domain (e.g., additive values, bounded numbers of agents), an EFX allocation exists for that very domain, providing a concrete pathway toward resolving this long standing open problem in fair division. Our third result establishes the existence of CEEI-with-floors when (i) n = 2 agents or (ii) n agents have identical valuations. If time permits, we will also discuss alternative combinatorial and randomized techniques that have been applied to the problem.

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